TY  - CONF
AU  - Perišić, Natalija
AU  - Jovanović, Radiša
AU  - Vesović, Mitra
AU  - Sretenović, Aleksandra
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7298
AB  - The use of artificial intelligence in modern agriculture is on the rise, due to the fact that it provides a possibility for more efficient production, better decision making and reduction of the costs. This research takes into consideration the use of the convolutional neural networks for diagnosing plant illnesses based on the leaf image. Detection of plant diseases in the early phase can improve the quality of the food products and minimize the loses. Convolutional neural networks are a type of deep learning method that is one of the most used models for solving image recognition, classification and detection tasks. Therefore, it is justified to anticipate that they can be very effectively applied in the agriculture sector. This paper covers plant species that are the most significant for Serbian production. Various models have been presented and analyzed, while highlighting their advantages and disadvantages when applied for solving this task.
C3  - ISAE 2023
T1  - Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image
EP  - 22
SP  - 13
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7298
ER  - 

@conference{
author = "Perišić, Natalija and Jovanović, Radiša and Vesović, Mitra and Sretenović, Aleksandra",
year = "2023",
abstract = "The use of artificial intelligence in modern agriculture is on the rise, due to the fact that it provides a possibility for more efficient production, better decision making and reduction of the costs. This research takes into consideration the use of the convolutional neural networks for diagnosing plant illnesses based on the leaf image. Detection of plant diseases in the early phase can improve the quality of the food products and minimize the loses. Convolutional neural networks are a type of deep learning method that is one of the most used models for solving image recognition, classification and detection tasks. Therefore, it is justified to anticipate that they can be very effectively applied in the agriculture sector. This paper covers plant species that are the most significant for Serbian production. Various models have been presented and analyzed, while highlighting their advantages and disadvantages when applied for solving this task.",
journal = "ISAE 2023",
title = "Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image",
pages = "22-13",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7298"
}

Perišić, N., Jovanović, R., Vesović, M.,& Sretenović, A.. (2023). Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image. in ISAE 2023, 13-22.
https://hdl.handle.net/21.15107/rcub_machinery_7298

Perišić N, Jovanović R, Vesović M, Sretenović A. Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image. in ISAE 2023. 2023;:13-22.
https://hdl.handle.net/21.15107/rcub_machinery_7298 .

Perišić, Natalija, Jovanović, Radiša, Vesović, Mitra, Sretenović, Aleksandra, "Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image" in ISAE 2023 (2023):13-22,
https://hdl.handle.net/21.15107/rcub_machinery_7298 .

TY  - CONF
AU  - Vesović, Mitra
AU  - Jovanović, Radiša
AU  - Perišić, Natalija
AU  - Sretenović, Aleksandra
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7297
AB  - Chamber dryers are widely used in various industries in order to remove the moisture from solid materials efficiently. Optimizing the design and operational parameters of chamber dryers plays a crucial role in enhancing their performance and energy efficiency. In order to maintain the temperature at the desired level, it is necessary to implement a good control system. To be able to facilitate the process of finding and setting parameters of the controller, for many control algorithms it is essential to make the reliable model of the object. The aim is to develop both reliable and accurate predictive model that can assist in optimizing the design, structures, and inspection processes of chamber dryers, which will lead to enhanced energy efficiency, harvesting and improved drying performance.
In this paper, the authors propose a novel approach for modeling heat flow transfer in chamber dryers using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The Quanser chamber was selected as the object of the research because of how closely its geometry, material choice, and air flow resemble the structural properties of a dryer. To obtain the most realistic model possible, parameters of ANFIS were found using Particle Swarm Optimization algorithm. By incorporating historical operational data of experimental measurements, the ANFIS model can learn and adapt to the dynamic behavior of the dryer system.
C3  - ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023
19th - 21st October 2023, Belgrade, Serbia
T1  - Modelling heat-flow prototype dryer using ANFIS optimized by PSO
EP  - 228
SP  - 219
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7297
ER  - 

@conference{
author = "Vesović, Mitra and Jovanović, Radiša and Perišić, Natalija and Sretenović, Aleksandra",
year = "2023",
abstract = "Chamber dryers are widely used in various industries in order to remove the moisture from solid materials efficiently. Optimizing the design and operational parameters of chamber dryers plays a crucial role in enhancing their performance and energy efficiency. In order to maintain the temperature at the desired level, it is necessary to implement a good control system. To be able to facilitate the process of finding and setting parameters of the controller, for many control algorithms it is essential to make the reliable model of the object. The aim is to develop both reliable and accurate predictive model that can assist in optimizing the design, structures, and inspection processes of chamber dryers, which will lead to enhanced energy efficiency, harvesting and improved drying performance.
In this paper, the authors propose a novel approach for modeling heat flow transfer in chamber dryers using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The Quanser chamber was selected as the object of the research because of how closely its geometry, material choice, and air flow resemble the structural properties of a dryer. To obtain the most realistic model possible, parameters of ANFIS were found using Particle Swarm Optimization algorithm. By incorporating historical operational data of experimental measurements, the ANFIS model can learn and adapt to the dynamic behavior of the dryer system.",
journal = "ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023
19th - 21st October 2023, Belgrade, Serbia",
title = "Modelling heat-flow prototype dryer using ANFIS optimized by PSO",
pages = "228-219",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7297"
}

Vesović, M., Jovanović, R., Perišić, N.,& Sretenović, A.. (2023). Modelling heat-flow prototype dryer using ANFIS optimized by PSO. in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023
19th - 21st October 2023, Belgrade, Serbia, 219-228.
https://hdl.handle.net/21.15107/rcub_machinery_7297

Vesović M, Jovanović R, Perišić N, Sretenović A. Modelling heat-flow prototype dryer using ANFIS optimized by PSO. in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023
19th - 21st October 2023, Belgrade, Serbia. 2023;:219-228.
https://hdl.handle.net/21.15107/rcub_machinery_7297 .

Vesović, Mitra, Jovanović, Radiša, Perišić, Natalija, Sretenović, Aleksandra, "Modelling heat-flow prototype dryer using ANFIS optimized by PSO" in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023
19th - 21st October 2023, Belgrade, Serbia (2023):219-228,
https://hdl.handle.net/21.15107/rcub_machinery_7297 .

TY  - THES
AU  - Nedeljković, Dušan
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7678
AB  - Integracija kibernetsko-fizičkih sistema (engl. Cyber-Physical Systems – CPS) u industrijski internet stvari predstavlja osnovu za prelazak sa centralizovanih na distribuirane sisteme upravljanja u okviru kojih se upravljački zadaci raspodeljuju na različite uređaje, a celokupan zadatak upravljanja realizuje kroz njihov sinhronizovani rad i stalnu razmenu informacija. Sveprisutna komunikacija između elemenata industrijskih sistema upravljanja (engl. Industrial Control Systems – ICS) kao i njihovo povezivanje na globalnu mrežu otvaraju prostor za različite kibernetske napade koji pored ekonomskih posledica i katastrofalnih oštećenja opreme mogu imati i negativne uticaje na životnu sredinu i bezbednost na radu. 
U fokusu ove doktorske disertacije je problem detekcije kibernetskih napada na komunikacione veze između CPS u okviru sistema za kontinualno upravljanje proizvodnim resursima. U radu je predložena metodologija za kreiranje sistema za detekciju napada koja je zasnovana na principima samonadgledanog učenja i kreiranju autoregresionih modela podataka koji se razmenjuju između uređaja u normalnim uslovima rada (bez napada) korišćenjem različitih tehnika mašinskog učenja. Metodologija vrši automatski izbor svih parametara algoritma za detekciju i uzima u obzir arhitekturu sistema upravljanja i mogućnost implementacije algoritma za detekciju napada na nekom od uređaja u okviru sistema. Može se primeniti kako za sisteme
iz kojih je moguće prikupiti dovoljnu količinu podataka, tako i za sisteme za koje je dostupnost podataka ograničena. 
Verifikacija razvijenih sistema za detekciju napada sprovedena je na javno dostupnim skupovima podataka i skupovima podataka dobijenim sa eksperimentalnih instalacija koje su razvijene u okviru disertacije. Izvršena je implementacija i eksperimentalna verifikacija sistema za detekciju napada generisanih korišćenjem razvijenih metoda na kreiranoj instalaciji čime su i u realnim uslovima potvrđene postavljene polazne hipoteze.
T2  - Univerzitet u Beogradu, Mašinski fakultet
T1  - Detekcija kibernetskih napada na sisteme za upravljanje proizvodnim resursima
T1  - Detection of cyber-attacks on systems for manufacturing equipment control
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7678
ER  - 

@phdthesis{
author = "Nedeljković, Dušan",
year = "2023",
abstract = "Integracija kibernetsko-fizičkih sistema (engl. Cyber-Physical Systems – CPS) u industrijski internet stvari predstavlja osnovu za prelazak sa centralizovanih na distribuirane sisteme upravljanja u okviru kojih se upravljački zadaci raspodeljuju na različite uređaje, a celokupan zadatak upravljanja realizuje kroz njihov sinhronizovani rad i stalnu razmenu informacija. Sveprisutna komunikacija između elemenata industrijskih sistema upravljanja (engl. Industrial Control Systems – ICS) kao i njihovo povezivanje na globalnu mrežu otvaraju prostor za različite kibernetske napade koji pored ekonomskih posledica i katastrofalnih oštećenja opreme mogu imati i negativne uticaje na životnu sredinu i bezbednost na radu. 
U fokusu ove doktorske disertacije je problem detekcije kibernetskih napada na komunikacione veze između CPS u okviru sistema za kontinualno upravljanje proizvodnim resursima. U radu je predložena metodologija za kreiranje sistema za detekciju napada koja je zasnovana na principima samonadgledanog učenja i kreiranju autoregresionih modela podataka koji se razmenjuju između uređaja u normalnim uslovima rada (bez napada) korišćenjem različitih tehnika mašinskog učenja. Metodologija vrši automatski izbor svih parametara algoritma za detekciju i uzima u obzir arhitekturu sistema upravljanja i mogućnost implementacije algoritma za detekciju napada na nekom od uređaja u okviru sistema. Može se primeniti kako za sisteme
iz kojih je moguće prikupiti dovoljnu količinu podataka, tako i za sisteme za koje je dostupnost podataka ograničena. 
Verifikacija razvijenih sistema za detekciju napada sprovedena je na javno dostupnim skupovima podataka i skupovima podataka dobijenim sa eksperimentalnih instalacija koje su razvijene u okviru disertacije. Izvršena je implementacija i eksperimentalna verifikacija sistema za detekciju napada generisanih korišćenjem razvijenih metoda na kreiranoj instalaciji čime su i u realnim uslovima potvrđene postavljene polazne hipoteze.",
journal = "Univerzitet u Beogradu, Mašinski fakultet",
title = "Detekcija kibernetskih napada na sisteme za upravljanje proizvodnim resursima, Detection of cyber-attacks on systems for manufacturing equipment control",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7678"
}

Nedeljković, D.. (2023). Detekcija kibernetskih napada na sisteme za upravljanje proizvodnim resursima. in Univerzitet u Beogradu, Mašinski fakultet.
https://hdl.handle.net/21.15107/rcub_machinery_7678

Nedeljković D. Detekcija kibernetskih napada na sisteme za upravljanje proizvodnim resursima. in Univerzitet u Beogradu, Mašinski fakultet. 2023;.
https://hdl.handle.net/21.15107/rcub_machinery_7678 .

Nedeljković, Dušan, "Detekcija kibernetskih napada na sisteme za upravljanje proizvodnim resursima" in Univerzitet u Beogradu, Mašinski fakultet (2023),
https://hdl.handle.net/21.15107/rcub_machinery_7678 .

TY  - CONF
AU  - Nedeljković, Dušan
AU  - Jakovljević, Živana
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7009
AB  - Industry 4.0 paradigm has brought about the changes in the way we manufacture. The integration of Cyber-Physical Systems into the Industrial Internet of Things represents the basis for the transition from traditionally centralized to distributed control systems where the overall control task is achieved through the cooperation of different devices which implies their mutual communication and constant information exchange. However, ubiquitous communication between devices with communication and computation capabilities opens up space for various cyber-attacks which can lead to catastrophic damage to equipment
and also can endanger the environment and human lives. Therefore, the development and implementation of cyber-attacks detection mechanisms are necessary to prevent negative effects. Deep learning (DL) techniques are successfully applied to generate models on which cyber-attacks detection algorithms are based. However, the size of the DL models is often unsuitable for implementation on industrial control devices that usually have significant computational constraints. The use of complex DL models may disrupt the operation of control systems and introduce unacceptable delays in real-time cyber-attacks detection algorithms. This paper explores the possibilities for application of knowledge distillation technique to generate lightweight DL models. These models are designed to align with the limitations of the devices on which they are deployed. The paper evaluates the performance of lightweight models in cyber-attacks detection algorithms, and compares them to algorithms based on DL models before distillation.
C3  - 39th International conference on production engineering of Serbia (ICPES 2023)
T1  - Generation of lightweight models for cyber-attacks detection algorithms using knowledge distillation
EP  - 31
SP  - 24
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7009
ER  - 

@conference{
author = "Nedeljković, Dušan and Jakovljević, Živana",
year = "2023",
abstract = "Industry 4.0 paradigm has brought about the changes in the way we manufacture. The integration of Cyber-Physical Systems into the Industrial Internet of Things represents the basis for the transition from traditionally centralized to distributed control systems where the overall control task is achieved through the cooperation of different devices which implies their mutual communication and constant information exchange. However, ubiquitous communication between devices with communication and computation capabilities opens up space for various cyber-attacks which can lead to catastrophic damage to equipment
and also can endanger the environment and human lives. Therefore, the development and implementation of cyber-attacks detection mechanisms are necessary to prevent negative effects. Deep learning (DL) techniques are successfully applied to generate models on which cyber-attacks detection algorithms are based. However, the size of the DL models is often unsuitable for implementation on industrial control devices that usually have significant computational constraints. The use of complex DL models may disrupt the operation of control systems and introduce unacceptable delays in real-time cyber-attacks detection algorithms. This paper explores the possibilities for application of knowledge distillation technique to generate lightweight DL models. These models are designed to align with the limitations of the devices on which they are deployed. The paper evaluates the performance of lightweight models in cyber-attacks detection algorithms, and compares them to algorithms based on DL models before distillation.",
journal = "39th International conference on production engineering of Serbia (ICPES 2023)",
title = "Generation of lightweight models for cyber-attacks detection algorithms using knowledge distillation",
pages = "31-24",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7009"
}

Nedeljković, D.,& Jakovljević, Ž.. (2023). Generation of lightweight models for cyber-attacks detection algorithms using knowledge distillation. in 39th International conference on production engineering of Serbia (ICPES 2023), 24-31.
https://hdl.handle.net/21.15107/rcub_machinery_7009

Nedeljković D, Jakovljević Ž. Generation of lightweight models for cyber-attacks detection algorithms using knowledge distillation. in 39th International conference on production engineering of Serbia (ICPES 2023). 2023;:24-31.
https://hdl.handle.net/21.15107/rcub_machinery_7009 .

Nedeljković, Dušan, Jakovljević, Živana, "Generation of lightweight models for cyber-attacks detection algorithms using knowledge distillation" in 39th International conference on production engineering of Serbia (ICPES 2023) (2023):24-31,
https://hdl.handle.net/21.15107/rcub_machinery_7009 .

TY  - CONF
AU  - Jokić, Aleksandar
AU  - Petrović, Milica
AU  - Miljković, Zoran
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7004
AB  - In recent years, metaheuristic algorithms have become increasingly advantageous for solving many real-world optimization-based engineering tasks. Integrated process planning and scheduling of machine tools and mobile robots utilized for transportation tasks in a manufacturing environment represents one such task. Since the number of solutions increases exponentially with the addition of either parts, machines, or robots, this task belongs to a group of NP-hard problems. Therefore, for its successful resolution, it is essential to use efficient algorithms that are able to explore vast solution space and provide optimal solutions. In this paper, we propose an algorithm for solving integrated scheduling of machine tools and mobile robots based on a novel arithmetic metaheuristic optimization. The arithmetic optimization algorithm belongs to a group of stochastic population-based algorithms inspired by arithmetic mathematical operations. The main advantage of the proposed algorithm is in a well-suited balance between exploration and exploitation phases that are appropriate for extremely hard multi-objective optimization. A multi-objective metric is utilized to evaluate obtained Pareto front solutions in terms of the exploration capabilities in the solution space. The proposed algorithm is compared with two other state-of-the-art metaheuristic algorithms. The experimental evaluation is carried out on 20 benchmark problems, and the results show the advantages of the proposed algorithm.
C3  - 39th International Conference on Production Engineering of Serbia (ICPES 2023)
T1  - The Arithmetic Optimization Algorithm for  Multi-Objective Mobile Robot Scheduling
EP  - 15
SP  - 9
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7004
ER  - 

@conference{
author = "Jokić, Aleksandar and Petrović, Milica and Miljković, Zoran",
year = "2023",
abstract = "In recent years, metaheuristic algorithms have become increasingly advantageous for solving many real-world optimization-based engineering tasks. Integrated process planning and scheduling of machine tools and mobile robots utilized for transportation tasks in a manufacturing environment represents one such task. Since the number of solutions increases exponentially with the addition of either parts, machines, or robots, this task belongs to a group of NP-hard problems. Therefore, for its successful resolution, it is essential to use efficient algorithms that are able to explore vast solution space and provide optimal solutions. In this paper, we propose an algorithm for solving integrated scheduling of machine tools and mobile robots based on a novel arithmetic metaheuristic optimization. The arithmetic optimization algorithm belongs to a group of stochastic population-based algorithms inspired by arithmetic mathematical operations. The main advantage of the proposed algorithm is in a well-suited balance between exploration and exploitation phases that are appropriate for extremely hard multi-objective optimization. A multi-objective metric is utilized to evaluate obtained Pareto front solutions in terms of the exploration capabilities in the solution space. The proposed algorithm is compared with two other state-of-the-art metaheuristic algorithms. The experimental evaluation is carried out on 20 benchmark problems, and the results show the advantages of the proposed algorithm.",
journal = "39th International Conference on Production Engineering of Serbia (ICPES 2023)",
title = "The Arithmetic Optimization Algorithm for  Multi-Objective Mobile Robot Scheduling",
pages = "15-9",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7004"
}

Jokić, A., Petrović, M.,& Miljković, Z.. (2023). The Arithmetic Optimization Algorithm for  Multi-Objective Mobile Robot Scheduling. in 39th International Conference on Production Engineering of Serbia (ICPES 2023), 9-15.
https://hdl.handle.net/21.15107/rcub_machinery_7004

Jokić A, Petrović M, Miljković Z. The Arithmetic Optimization Algorithm for  Multi-Objective Mobile Robot Scheduling. in 39th International Conference on Production Engineering of Serbia (ICPES 2023). 2023;:9-15.
https://hdl.handle.net/21.15107/rcub_machinery_7004 .

Jokić, Aleksandar, Petrović, Milica, Miljković, Zoran, "The Arithmetic Optimization Algorithm for  Multi-Objective Mobile Robot Scheduling" in 39th International Conference on Production Engineering of Serbia (ICPES 2023) (2023):9-15,
https://hdl.handle.net/21.15107/rcub_machinery_7004 .

TY  - CONF
AU  - Sretenović, Aleksandra
AU  - Jovanović, Radiša
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7296
AB  - This paper covers the application of artificial intelligence in agriculture. Technology development has enabled measurement, collecting and processing high quality big data. These data can be successfully used to significantly improve numerous segments of agriculture sector. The accent in this paper is given on the models used for energy use prediction. The application of Artificial Neural Networks with different structure is presented, such as Feedforward Neural Network, Radial basis Function Network and Adaptive Neuro-Fuzzy Inference System. Support Vector Machine model is also shown. The improvements of individual models are elaborated, through the analysis of the ensemble and hybrid approach. All of the proposed models are capable of solving complex problem of prediction of energy use based on real, measured data. Ensemble and hybrid models are promising, as it has been shown that the prediction accuracy is improved by combining different single models in proposed manner.
C3  - ISAE 2023
T1  - Artificial intelligence methods for energy use prediction
SP  - 42
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7296
ER  - 

@conference{
author = "Sretenović, Aleksandra and Jovanović, Radiša",
year = "2023",
abstract = "This paper covers the application of artificial intelligence in agriculture. Technology development has enabled measurement, collecting and processing high quality big data. These data can be successfully used to significantly improve numerous segments of agriculture sector. The accent in this paper is given on the models used for energy use prediction. The application of Artificial Neural Networks with different structure is presented, such as Feedforward Neural Network, Radial basis Function Network and Adaptive Neuro-Fuzzy Inference System. Support Vector Machine model is also shown. The improvements of individual models are elaborated, through the analysis of the ensemble and hybrid approach. All of the proposed models are capable of solving complex problem of prediction of energy use based on real, measured data. Ensemble and hybrid models are promising, as it has been shown that the prediction accuracy is improved by combining different single models in proposed manner.",
journal = "ISAE 2023",
title = "Artificial intelligence methods for energy use prediction",
pages = "42",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7296"
}

Sretenović, A.,& Jovanović, R.. (2023). Artificial intelligence methods for energy use prediction. in ISAE 2023, 42.
https://hdl.handle.net/21.15107/rcub_machinery_7296

Sretenović A, Jovanović R. Artificial intelligence methods for energy use prediction. in ISAE 2023. 2023;:42.
https://hdl.handle.net/21.15107/rcub_machinery_7296 .

Sretenović, Aleksandra, Jovanović, Radiša, "Artificial intelligence methods for energy use prediction" in ISAE 2023 (2023):42,
https://hdl.handle.net/21.15107/rcub_machinery_7296 .

TY  - CONF
AU  - Kerčov, Anton
AU  - Jovanović, Radiša
AU  - Bajc, Tamara
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7076
AB  - Compared to methodology provided by standards concerning thermal comfort, by using
models based on various approximation methods or artificial intelligence, it may be possible
to ensure more time efficient and accurate calculation of thermal comfort indices. The aim of
this study is to compare Predicted Mean Vote (PMV) computation model established by using
multiple linear regression and trained artificial neural network, from the standpoint of
accuracy. Both models are established on the basis of the same dataset which consists of 400
combinations of 4 thermal comfort parameters. These parameters are the air temperature,
mean radiant temperature, relative humidity and clothing resistance, while activity level and
air velocity are adopted as 1.1 met (office typing activity) and 0.05 m/s, respectively, and are
considered constant values for selected type of indoor environment. Clothing resistance is
adopted as 0.5 clo for summer period and 1.0 clo for winter period, while the air temperature,
mean radiant temperature and relative humidity are values which are randomly generated
within appropriately selected ranges. Taking into account that coefficients of determination
which correspond to it are over 95%, resulting first degree polynomial relation obtained by
using multiple linear regression can be considered a satisfactory approximation of PMV
model as it is given in ASHRAE Standard 55-2020. Furthermore, there are certain input value
combinations for which PMV values obtained by using this model coincide with the ones
calculated by using algorithm which is provided by standard. However, results obtained by
using trained neural network with one hidden layer coincide with PMV values calculated on
the basis of ASHRAE Standard 55-2020 for each input value combination. Therefore, from
the standpoint of accuracy, it is concluded that neural network provides significantly better
approximation of PMV model.
PB  - Faculty of Mechanical Engineering and Naval Architecture, Zagreb
C3  - 18th conference on sustainable development of energy, water and environment systems
T1  - Thermal comfort indices analysis using multiple linear regression and neural network
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7076
ER  - 

@conference{
author = "Kerčov, Anton and Jovanović, Radiša and Bajc, Tamara",
year = "2023",
abstract = "Compared to methodology provided by standards concerning thermal comfort, by using
models based on various approximation methods or artificial intelligence, it may be possible
to ensure more time efficient and accurate calculation of thermal comfort indices. The aim of
this study is to compare Predicted Mean Vote (PMV) computation model established by using
multiple linear regression and trained artificial neural network, from the standpoint of
accuracy. Both models are established on the basis of the same dataset which consists of 400
combinations of 4 thermal comfort parameters. These parameters are the air temperature,
mean radiant temperature, relative humidity and clothing resistance, while activity level and
air velocity are adopted as 1.1 met (office typing activity) and 0.05 m/s, respectively, and are
considered constant values for selected type of indoor environment. Clothing resistance is
adopted as 0.5 clo for summer period and 1.0 clo for winter period, while the air temperature,
mean radiant temperature and relative humidity are values which are randomly generated
within appropriately selected ranges. Taking into account that coefficients of determination
which correspond to it are over 95%, resulting first degree polynomial relation obtained by
using multiple linear regression can be considered a satisfactory approximation of PMV
model as it is given in ASHRAE Standard 55-2020. Furthermore, there are certain input value
combinations for which PMV values obtained by using this model coincide with the ones
calculated by using algorithm which is provided by standard. However, results obtained by
using trained neural network with one hidden layer coincide with PMV values calculated on
the basis of ASHRAE Standard 55-2020 for each input value combination. Therefore, from
the standpoint of accuracy, it is concluded that neural network provides significantly better
approximation of PMV model.",
publisher = "Faculty of Mechanical Engineering and Naval Architecture, Zagreb",
journal = "18th conference on sustainable development of energy, water and environment systems",
title = "Thermal comfort indices analysis using multiple linear regression and neural network",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7076"
}

Kerčov, A., Jovanović, R.,& Bajc, T.. (2023). Thermal comfort indices analysis using multiple linear regression and neural network. in 18th conference on sustainable development of energy, water and environment systems
Faculty of Mechanical Engineering and Naval Architecture, Zagreb..
https://hdl.handle.net/21.15107/rcub_machinery_7076

Kerčov A, Jovanović R, Bajc T. Thermal comfort indices analysis using multiple linear regression and neural network. in 18th conference on sustainable development of energy, water and environment systems. 2023;.
https://hdl.handle.net/21.15107/rcub_machinery_7076 .

Kerčov, Anton, Jovanović, Radiša, Bajc, Tamara, "Thermal comfort indices analysis using multiple linear regression and neural network" in 18th conference on sustainable development of energy, water and environment systems (2023),
https://hdl.handle.net/21.15107/rcub_machinery_7076 .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Nedeljković, Dušan
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/6883
AB  - The fourth industrial revolution known as Industry 4.0 brings digitalization of manufacturing processes to a new
level through ubiquitous interconnection and real-time information flow between information technologies (IT) and
operational technologies (OT) as parts of Industrial Control Systems (ICS). This information flow is not limited to but expands beyond factory walls enabling manufacturing systems to adapt quickly and efficiently to changing customer demands and diversified products. The adaptation is carried out through physical and/or functional reconfiguration of manufacturing systems where Industrial Internet of Things (IIoT) based on Cyber-Physical Systems (CPS) represents the key technical enabler. These changes result in a transition from centralized to distributed control systems architecture where the whole control task is achieved through intensive cooperation between smart devices (e.g., sensors and actuators) with integrated communication and computation capabilities. However, introducing IIoT in ICS brings about new cybersecurity issues due to increased communication between system elements and connection to the global network, making ICS vulnerable to different cyber-attacks with potentially catastrophic consequences. Recently, the research in ICS cybersecurity has intensified leading to significant results for continuous time and
discrete events-controlled systems. However, cybersecurity issues in motion control systems that are frequently employed in different manufacturing resources such as machine tools and industrial robots were not sufficiently explored. This work provides an overview of the cybersecurity related challenges in motion control tasks.
C3  - 10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2023), Proceedings, Sarajevo, B&H, June 2023, ROI1.5, 2023
T1  - Cybersecurity issues in motion control – an overview of challenges
SP  - ROI1.5, 1-6
UR  - https://hdl.handle.net/21.15107/rcub_machinery_6883
ER  - 

@conference{
author = "Jakovljević, Živana and Nedeljković, Dušan",
year = "2023",
abstract = "The fourth industrial revolution known as Industry 4.0 brings digitalization of manufacturing processes to a new
level through ubiquitous interconnection and real-time information flow between information technologies (IT) and
operational technologies (OT) as parts of Industrial Control Systems (ICS). This information flow is not limited to but expands beyond factory walls enabling manufacturing systems to adapt quickly and efficiently to changing customer demands and diversified products. The adaptation is carried out through physical and/or functional reconfiguration of manufacturing systems where Industrial Internet of Things (IIoT) based on Cyber-Physical Systems (CPS) represents the key technical enabler. These changes result in a transition from centralized to distributed control systems architecture where the whole control task is achieved through intensive cooperation between smart devices (e.g., sensors and actuators) with integrated communication and computation capabilities. However, introducing IIoT in ICS brings about new cybersecurity issues due to increased communication between system elements and connection to the global network, making ICS vulnerable to different cyber-attacks with potentially catastrophic consequences. Recently, the research in ICS cybersecurity has intensified leading to significant results for continuous time and
discrete events-controlled systems. However, cybersecurity issues in motion control systems that are frequently employed in different manufacturing resources such as machine tools and industrial robots were not sufficiently explored. This work provides an overview of the cybersecurity related challenges in motion control tasks.",
journal = "10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2023), Proceedings, Sarajevo, B&H, June 2023, ROI1.5, 2023",
title = "Cybersecurity issues in motion control – an overview of challenges",
pages = "ROI1.5, 1-6",
url = "https://hdl.handle.net/21.15107/rcub_machinery_6883"
}

Jakovljević, Ž.,& Nedeljković, D.. (2023). Cybersecurity issues in motion control – an overview of challenges. in 10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2023), Proceedings, Sarajevo, B&H, June 2023, ROI1.5, 2023, ROI1.5, 1-6.
https://hdl.handle.net/21.15107/rcub_machinery_6883

Jakovljević Ž, Nedeljković D. Cybersecurity issues in motion control – an overview of challenges. in 10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2023), Proceedings, Sarajevo, B&H, June 2023, ROI1.5, 2023. 2023;:ROI1.5, 1-6.
https://hdl.handle.net/21.15107/rcub_machinery_6883 .

Jakovljević, Živana, Nedeljković, Dušan, "Cybersecurity issues in motion control – an overview of challenges" in 10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2023), Proceedings, Sarajevo, B&H, June 2023, ROI1.5, 2023 (2023):ROI1.5, 1-6,
https://hdl.handle.net/21.15107/rcub_machinery_6883 .

TY  - CONF
AU  - Nedeljković, Dušan
AU  - Jakovljević, Živana
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/6884
AB  - With the introduction of Cyber Physical Systems and Industrial Internet of Things within Industry 4.0, vision systems, as indispensable element for robot cognition, become smart devices integrated into the control system using different communication links. In this control framework image streams are transferred between elements of distributed control system opening the possibility for various cyber-attacks that can cause changes in certain parts of images eventually triggering wrong decisions and negative consequences to the system
performance. Timely detection of the attacks on communicated image streams is necessary to mitigate or completely avoid their negative effects. In this paper we propose a method for the prediction of the next image in the sequence which can be utilized for the development of anomaly-based cyber-attack detection mechanisms. For the model generation, we have explored the application of several deep learning architectures based on two-dimensional Convolutional Neural Networks and Convolutional Long Short-Term Memory Recurrent Neural Networks. Images obtained from the real-world experimental installation were utilized for model design. Our deep learning models proved to be effective in predicting the next frames according to the criteria of a discrepancy between pixels of the real and estimated images.
C3  - 32nd International Conference on Robotics in Alpe-Adria-Danube Region, June 14-16, Bled, Slovenia, 2023.
T1  - Deep learning prediction models for the detection of cyber-attacks on image sequences
EP  - 70
SP  - 62
DO  - 10.1007/978-3-031-32606-6_8
ER  - 

@conference{
author = "Nedeljković, Dušan and Jakovljević, Živana",
year = "2023",
abstract = "With the introduction of Cyber Physical Systems and Industrial Internet of Things within Industry 4.0, vision systems, as indispensable element for robot cognition, become smart devices integrated into the control system using different communication links. In this control framework image streams are transferred between elements of distributed control system opening the possibility for various cyber-attacks that can cause changes in certain parts of images eventually triggering wrong decisions and negative consequences to the system
performance. Timely detection of the attacks on communicated image streams is necessary to mitigate or completely avoid their negative effects. In this paper we propose a method for the prediction of the next image in the sequence which can be utilized for the development of anomaly-based cyber-attack detection mechanisms. For the model generation, we have explored the application of several deep learning architectures based on two-dimensional Convolutional Neural Networks and Convolutional Long Short-Term Memory Recurrent Neural Networks. Images obtained from the real-world experimental installation were utilized for model design. Our deep learning models proved to be effective in predicting the next frames according to the criteria of a discrepancy between pixels of the real and estimated images.",
journal = "32nd International Conference on Robotics in Alpe-Adria-Danube Region, June 14-16, Bled, Slovenia, 2023.",
title = "Deep learning prediction models for the detection of cyber-attacks on image sequences",
pages = "70-62",
doi = "10.1007/978-3-031-32606-6_8"
}

Nedeljković, D.,& Jakovljević, Ž.. (2023). Deep learning prediction models for the detection of cyber-attacks on image sequences. in 32nd International Conference on Robotics in Alpe-Adria-Danube Region, June 14-16, Bled, Slovenia, 2023., 62-70.
https://doi.org/10.1007/978-3-031-32606-6_8

Nedeljković D, Jakovljević Ž. Deep learning prediction models for the detection of cyber-attacks on image sequences. in 32nd International Conference on Robotics in Alpe-Adria-Danube Region, June 14-16, Bled, Slovenia, 2023.. 2023;:62-70.
doi:10.1007/978-3-031-32606-6_8 .

Nedeljković, Dušan, Jakovljević, Živana, "Deep learning prediction models for the detection of cyber-attacks on image sequences" in 32nd International Conference on Robotics in Alpe-Adria-Danube Region, June 14-16, Bled, Slovenia, 2023. (2023):62-70,
https://doi.org/10.1007/978-3-031-32606-6_8 . .

TY  - JOUR
AU  - Jovanović, Radiša
AU  - Zarić, Vladimir
AU  - Bučevac, Zoran
AU  - Bugarić, Uglješa
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4524
AB  - The study proposes a novel method for synthesis of a discrete-time parallel distributed
compensation (PDC) controller for the nonlinear discrete-time Takagi–Sugeno (TS) fuzzy plant model. For each of the fuzzy plant model linear subsystems, a local linear first order proportional-sum (PS) controller is designed. The algebraic technique is used in two-dimensional parameter space, utilizing the characteristic polynomial of the row nondegenerate full transfer function matrix. Each system’s relative stability is accomplished in relation to the selected damping coefficient. The supplementary criterion is the minimal value of the performance index in the form of the sum of squared errors (SSE). However, unlike the traditional technique, output error is influenced by all simultaneous actions on the system: nonzero inputs and nonzero initial conditions. The full transfer function matrix of the system allows for the treatment of simultaneous actions of the input vector and unknown unpredictable initial conditions. In order to show the improvement caused by the application of a new optimization method that considers nonzero initial conditions, a comparison of PDC controllers designed under zero and nonzero initial conditions is given, where the system in both cases starts from the same nonzero initial conditions, which is often the case in practice. The simulation and experimental results on a DC servo motor are shown to demonstrate the suggested method efficiency.
PB  - MDPI
T2  - Applied Sciences
T1  - Discrete-time system conditional optimization based on Takagi-Sugeno fuzzy model using the full transfer function
EP  - 22
IS  - 7705
SP  - 1
VL  - 12
DO  - 10.3390/app12157705
ER  - 

@article{
author = "Jovanović, Radiša and Zarić, Vladimir and Bučevac, Zoran and Bugarić, Uglješa",
year = "2022",
abstract = "The study proposes a novel method for synthesis of a discrete-time parallel distributed
compensation (PDC) controller for the nonlinear discrete-time Takagi–Sugeno (TS) fuzzy plant model. For each of the fuzzy plant model linear subsystems, a local linear first order proportional-sum (PS) controller is designed. The algebraic technique is used in two-dimensional parameter space, utilizing the characteristic polynomial of the row nondegenerate full transfer function matrix. Each system’s relative stability is accomplished in relation to the selected damping coefficient. The supplementary criterion is the minimal value of the performance index in the form of the sum of squared errors (SSE). However, unlike the traditional technique, output error is influenced by all simultaneous actions on the system: nonzero inputs and nonzero initial conditions. The full transfer function matrix of the system allows for the treatment of simultaneous actions of the input vector and unknown unpredictable initial conditions. In order to show the improvement caused by the application of a new optimization method that considers nonzero initial conditions, a comparison of PDC controllers designed under zero and nonzero initial conditions is given, where the system in both cases starts from the same nonzero initial conditions, which is often the case in practice. The simulation and experimental results on a DC servo motor are shown to demonstrate the suggested method efficiency.",
publisher = "MDPI",
journal = "Applied Sciences",
title = "Discrete-time system conditional optimization based on Takagi-Sugeno fuzzy model using the full transfer function",
pages = "22-1",
number = "7705",
volume = "12",
doi = "10.3390/app12157705"
}

Jovanović, R., Zarić, V., Bučevac, Z.,& Bugarić, U.. (2022). Discrete-time system conditional optimization based on Takagi-Sugeno fuzzy model using the full transfer function. in Applied Sciences
MDPI., 12(7705), 1-22.
https://doi.org/10.3390/app12157705

Jovanović R, Zarić V, Bučevac Z, Bugarić U. Discrete-time system conditional optimization based on Takagi-Sugeno fuzzy model using the full transfer function. in Applied Sciences. 2022;12(7705):1-22.
doi:10.3390/app12157705 .

Jovanović, Radiša, Zarić, Vladimir, Bučevac, Zoran, Bugarić, Uglješa, "Discrete-time system conditional optimization based on Takagi-Sugeno fuzzy model using the full transfer function" in Applied Sciences, 12, no. 7705 (2022):1-22,
https://doi.org/10.3390/app12157705 . .

TY  - JOUR
AU  - Jovanović, Radiša
AU  - Zarić, Vladimir
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3781
AB  - Even though, it is mostly used by process control engineers, the temperature control remains an important task for researchers. This paper addressed two separate issues concerning model optimization and control. Firstly, the linear models for the three different operating points of the heat flow system were found. From these identified models a Takagi-Sugeno model is obtained using fixed membership functions in the premises of the rules. According to the chosen objective function, parameters in the premise part of Takagi-Sugeno fuzzy model were optimized using the grey wolf algorithm. Furthermore, by using the parallel distributed compensation a fuzzy controller is developed via the fuzzy blending of three proportional + sum controllers designed for each of the operating points. In order to evaluate performance, a comparison is made between the fuzzy controller and local linear controllers. Moreover, the fuzzy controllers from the optimized and initial Takagi-Sugeno plant models are compared. The experimental results on a heat flow platform are presented to validate efficiency of the proposed method.
PB  - Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd
T2  - Thermal Science
T1  - Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer
EP  - 2286
IS  - 3
SP  - 2275
VL  - 26
DO  - 10.2298/TSCI210825324J
ER  - 

@article{
author = "Jovanović, Radiša and Zarić, Vladimir",
year = "2022",
abstract = "Even though, it is mostly used by process control engineers, the temperature control remains an important task for researchers. This paper addressed two separate issues concerning model optimization and control. Firstly, the linear models for the three different operating points of the heat flow system were found. From these identified models a Takagi-Sugeno model is obtained using fixed membership functions in the premises of the rules. According to the chosen objective function, parameters in the premise part of Takagi-Sugeno fuzzy model were optimized using the grey wolf algorithm. Furthermore, by using the parallel distributed compensation a fuzzy controller is developed via the fuzzy blending of three proportional + sum controllers designed for each of the operating points. In order to evaluate performance, a comparison is made between the fuzzy controller and local linear controllers. Moreover, the fuzzy controllers from the optimized and initial Takagi-Sugeno plant models are compared. The experimental results on a heat flow platform are presented to validate efficiency of the proposed method.",
publisher = "Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd",
journal = "Thermal Science",
title = "Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer",
pages = "2286-2275",
number = "3",
volume = "26",
doi = "10.2298/TSCI210825324J"
}

Jovanović, R.,& Zarić, V.. (2022). Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer. in Thermal Science
Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd., 26(3), 2275-2286.
https://doi.org/10.2298/TSCI210825324J

Jovanović R, Zarić V. Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer. in Thermal Science. 2022;26(3):2275-2286.
doi:10.2298/TSCI210825324J .

Jovanović, Radiša, Zarić, Vladimir, "Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer" in Thermal Science, 26, no. 3 (2022):2275-2286,
https://doi.org/10.2298/TSCI210825324J . .

TY  - JOUR
AU  - Zarić, Vladimir
AU  - Bučevac, Zoran M.
AU  - Jovanović, Radiša
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3771
AB  - The paper presents a new approach to the design of the classical PD controller for the plant in the closed loop control system. Proposed controller has two unknown adjustable parameters which are designed by the algebraic method in the two dimensional parameter space, by using the newly discovered characteristic polynomial of the row nondegenerate full transfer function matrix. The system relative stability, in regard to the chosen damping coefficient is achieved. The optimality criterion is the minimal value of the performance index and sum of squared error is taken as an objective function. The output error used in the performance index is influenced by all actions on the system at the same time: by nonzero initial conditions and by nonzero inputs. In the classical approach the output error is influenced only by nonzero inputs. Experimental results confirm that by taking into account nonzero initial conditions, an optimal solution is obtained, which is not the case with the classical method where optimization is performed at zero initial conditions.
PB  - Univ Osijek, Tech Fac, Slavonski Brod
T2  - Tehnički vjesnik
T1  - Discrete-Time System Conditional Optimization in the Parameter Space with Nonzero Initial Conditions
EP  - 207
IS  - 1
SP  - 200
VL  - 29
DO  - 10.17559/TV-20191031145233
ER  - 

@article{
author = "Zarić, Vladimir and Bučevac, Zoran M. and Jovanović, Radiša",
year = "2022",
abstract = "The paper presents a new approach to the design of the classical PD controller for the plant in the closed loop control system. Proposed controller has two unknown adjustable parameters which are designed by the algebraic method in the two dimensional parameter space, by using the newly discovered characteristic polynomial of the row nondegenerate full transfer function matrix. The system relative stability, in regard to the chosen damping coefficient is achieved. The optimality criterion is the minimal value of the performance index and sum of squared error is taken as an objective function. The output error used in the performance index is influenced by all actions on the system at the same time: by nonzero initial conditions and by nonzero inputs. In the classical approach the output error is influenced only by nonzero inputs. Experimental results confirm that by taking into account nonzero initial conditions, an optimal solution is obtained, which is not the case with the classical method where optimization is performed at zero initial conditions.",
publisher = "Univ Osijek, Tech Fac, Slavonski Brod",
journal = "Tehnički vjesnik",
title = "Discrete-Time System Conditional Optimization in the Parameter Space with Nonzero Initial Conditions",
pages = "207-200",
number = "1",
volume = "29",
doi = "10.17559/TV-20191031145233"
}

Zarić, V., Bučevac, Z. M.,& Jovanović, R.. (2022). Discrete-Time System Conditional Optimization in the Parameter Space with Nonzero Initial Conditions. in Tehnički vjesnik
Univ Osijek, Tech Fac, Slavonski Brod., 29(1), 200-207.
https://doi.org/10.17559/TV-20191031145233

Zarić V, Bučevac ZM, Jovanović R. Discrete-Time System Conditional Optimization in the Parameter Space with Nonzero Initial Conditions. in Tehnički vjesnik. 2022;29(1):200-207.
doi:10.17559/TV-20191031145233 .

Zarić, Vladimir, Bučevac, Zoran M., Jovanović, Radiša, "Discrete-Time System Conditional Optimization in the Parameter Space with Nonzero Initial Conditions" in Tehnički vjesnik, 29, no. 1 (2022):200-207,
https://doi.org/10.17559/TV-20191031145233 . .

TY  - JOUR
AU  - Lesi, Vuk
AU  - Jakovljević, Živana
AU  - Pajić, Miroslav
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/101
AB  - Internet of Things (IoT) technologies enable development of reconfigurable manufacturing systems--a new generation of modularized industrial equipment suitable for highly customized manufacturing. Sequential control in these systems is largely based on discrete events, whereas their formal execution semantics is specified as control interpreted Petri nets (CIPN). Despite industry-wide use of programming languages based on the CIPN formalism, formal verification of such control applications in the presence of adversarial activity is not supported. Consequently, in this article, we introduce security-aware modeling and verification techniques for CIPN-based sequential control applications. Specifically, we show how CIPN models of networked industrial IoT controllers can be transformed into time Petri net (TPN)-based models and composed with plant and security-aware channel models in order to enable system-level verification of safety properties in the presence of network-based attacks. Additionally, we introduce realistic channel-specific attack models that capture adversarial behavior using nondeterminism. Moreover, we show how verification results can be utilized to introduce security patches and facilitate design of attack detectors that improve system resiliency and enable satisfaction of critical safety properties. Finally, we evaluate our framework on an industrial case study.
PB  - IEEE - Inst Electrical Electronics Engineers Inc, Piscataway
T2  - IEEE Transactions on Automation Science and Engineering
T1  - Security Analysis for Distributed IoT-Based Industrial Automation
EP  - 3108
IS  - 4
SP  - 3093
VL  - 19
DO  - 10.1109/TASE.2021.3106335
ER  - 

@article{
author = "Lesi, Vuk and Jakovljević, Živana and Pajić, Miroslav",
year = "2022",
abstract = "Internet of Things (IoT) technologies enable development of reconfigurable manufacturing systems--a new generation of modularized industrial equipment suitable for highly customized manufacturing. Sequential control in these systems is largely based on discrete events, whereas their formal execution semantics is specified as control interpreted Petri nets (CIPN). Despite industry-wide use of programming languages based on the CIPN formalism, formal verification of such control applications in the presence of adversarial activity is not supported. Consequently, in this article, we introduce security-aware modeling and verification techniques for CIPN-based sequential control applications. Specifically, we show how CIPN models of networked industrial IoT controllers can be transformed into time Petri net (TPN)-based models and composed with plant and security-aware channel models in order to enable system-level verification of safety properties in the presence of network-based attacks. Additionally, we introduce realistic channel-specific attack models that capture adversarial behavior using nondeterminism. Moreover, we show how verification results can be utilized to introduce security patches and facilitate design of attack detectors that improve system resiliency and enable satisfaction of critical safety properties. Finally, we evaluate our framework on an industrial case study.",
publisher = "IEEE - Inst Electrical Electronics Engineers Inc, Piscataway",
journal = "IEEE Transactions on Automation Science and Engineering",
title = "Security Analysis for Distributed IoT-Based Industrial Automation",
pages = "3108-3093",
number = "4",
volume = "19",
doi = "10.1109/TASE.2021.3106335"
}

Lesi, V., Jakovljević, Ž.,& Pajić, M.. (2022). Security Analysis for Distributed IoT-Based Industrial Automation. in IEEE Transactions on Automation Science and Engineering
IEEE - Inst Electrical Electronics Engineers Inc, Piscataway., 19(4), 3093-3108.
https://doi.org/10.1109/TASE.2021.3106335

Lesi V, Jakovljević Ž, Pajić M. Security Analysis for Distributed IoT-Based Industrial Automation. in IEEE Transactions on Automation Science and Engineering. 2022;19(4):3093-3108.
doi:10.1109/TASE.2021.3106335 .

Lesi, Vuk, Jakovljević, Živana, Pajić, Miroslav, "Security Analysis for Distributed IoT-Based Industrial Automation" in IEEE Transactions on Automation Science and Engineering, 19, no. 4 (2022):3093-3108,
https://doi.org/10.1109/TASE.2021.3106335 . .

TY  - CONF
AU  - Vesović, Mitra
AU  - Jovanović, Radiša
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4546
AB  - Several studies dealing with position control of the DC motor have reported 
issues concerning friction force. This article demonstrates a nonlinear control 
and optimization strategy for position control of a series servo motor. Once it is 
empirically verified that the linear model does not adequately reflect the system, 
the model is upgraded from linear to nonlinear. In the course of the research, 
the nonlinear feedback linearizing the controller's behavior is examined. A grey 
wolf metaheuristic optimization algorithm is used to find the coefficients of the 
controller's gains. In this way, modern methods are applied to take a fresh look 
at the existing problem.  Furthermore, performance for various targeted output 
signals is compared to show the approach proposed in the study. Also, a compara-
tive analysis with whale optimization algorithm is performed. The experimental 
results acquired on the stated system are shown, and they validate the usage of the 
nonlinear control, demonstrating the effectiveness of using optimum feedback 
linearization in electrical machines.
PB  - Belgrade :  Singidunum University
C3  - Sinteza 2022-International Scientific Conference on Information Technology and Data Related Research
T1  - GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN  BY FEEDBACK LINEARIZATION METHOD
EP  - 43
SP  - THEORETICAL COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE SESSION pp. 36
DO  - 10.15308/Sinteza-2022-36-43
ER  - 

@conference{
author = "Vesović, Mitra and Jovanović, Radiša",
year = "2022",
abstract = "Several studies dealing with position control of the DC motor have reported 
issues concerning friction force. This article demonstrates a nonlinear control 
and optimization strategy for position control of a series servo motor. Once it is 
empirically verified that the linear model does not adequately reflect the system, 
the model is upgraded from linear to nonlinear. In the course of the research, 
the nonlinear feedback linearizing the controller's behavior is examined. A grey 
wolf metaheuristic optimization algorithm is used to find the coefficients of the 
controller's gains. In this way, modern methods are applied to take a fresh look 
at the existing problem.  Furthermore, performance for various targeted output 
signals is compared to show the approach proposed in the study. Also, a compara-
tive analysis with whale optimization algorithm is performed. The experimental 
results acquired on the stated system are shown, and they validate the usage of the 
nonlinear control, demonstrating the effectiveness of using optimum feedback 
linearization in electrical machines.",
publisher = "Belgrade :  Singidunum University",
journal = "Sinteza 2022-International Scientific Conference on Information Technology and Data Related Research",
title = "GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN  BY FEEDBACK LINEARIZATION METHOD",
pages = "43-THEORETICAL COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE SESSION pp. 36",
doi = "10.15308/Sinteza-2022-36-43"
}

Vesović, M.,& Jovanović, R.. (2022). GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN  BY FEEDBACK LINEARIZATION METHOD. in Sinteza 2022-International Scientific Conference on Information Technology and Data Related Research
Belgrade :  Singidunum University., THEORETICAL COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE SESSION pp. 36-43.
https://doi.org/10.15308/Sinteza-2022-36-43

Vesović M, Jovanović R. GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN  BY FEEDBACK LINEARIZATION METHOD. in Sinteza 2022-International Scientific Conference on Information Technology and Data Related Research. 2022;:THEORETICAL COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE SESSION pp. 36-43.
doi:10.15308/Sinteza-2022-36-43 .

Vesović, Mitra, Jovanović, Radiša, "GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN  BY FEEDBACK LINEARIZATION METHOD" in Sinteza 2022-International Scientific Conference on Information Technology and Data Related Research (2022):THEORETICAL COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE SESSION pp. 36-43,
https://doi.org/10.15308/Sinteza-2022-36-43 . .

TY  - JOUR
AU  - Jovanović, Radiša
AU  - Bugarić, Uglješa
AU  - Vesović, Mitra 
AU  - Perišić, Natalija
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4516
AB  - This paper presents the proportional–derivative fuzzy controller for
trajectory tracking of the gripping mechanism with two degrees of
freedom. Aiming to achieve movement of the gripping mechanism without
sudden starting and stopping, a polynomial velocity profile is utilized. The
African vultures optimization, as one of the latest metaheuristic
algorithms, is used to obtain the optimal input/output scaling gains of the
proposed fuzzy controller according to the selected fitness function. The
results obtained by this algorithm are compared with the other three new
and popular metaheuristic algorithms: the whale optimization, the ant lion
optimization and the sine cosine algorithm. Moreover, a simulation study
was done for the defined initial position and for the scenario where there is
a certain deviation because the gripping mechanism is not at its original
initial position. Finally, the robustness of the controller is tested for the
case when the masses of the segments increase three times. The results
revealed that the suggested controller was capable of dealing with
nonlinearities of the gripping mechanism, initial position and parameter
changes. The movement of the gripping mechanism is smooth and follows
the defined trajectory.
PB  - University of Belgrade - Faculty of Mechanical Engineering
T2  - FME Transactions
T1  - Fuzzy Controller Optimized by the African Vultures Algorithm for Trajectory Tracking of a Two–Link Gripping Mechanism
EP  - 501
IS  - 3
SP  - 491
VL  - 50
DO  - 10.5937/fme2203491J
ER  - 

@article{
author = "Jovanović, Radiša and Bugarić, Uglješa and Vesović, Mitra  and Perišić, Natalija",
year = "2022",
abstract = "This paper presents the proportional–derivative fuzzy controller for
trajectory tracking of the gripping mechanism with two degrees of
freedom. Aiming to achieve movement of the gripping mechanism without
sudden starting and stopping, a polynomial velocity profile is utilized. The
African vultures optimization, as one of the latest metaheuristic
algorithms, is used to obtain the optimal input/output scaling gains of the
proposed fuzzy controller according to the selected fitness function. The
results obtained by this algorithm are compared with the other three new
and popular metaheuristic algorithms: the whale optimization, the ant lion
optimization and the sine cosine algorithm. Moreover, a simulation study
was done for the defined initial position and for the scenario where there is
a certain deviation because the gripping mechanism is not at its original
initial position. Finally, the robustness of the controller is tested for the
case when the masses of the segments increase three times. The results
revealed that the suggested controller was capable of dealing with
nonlinearities of the gripping mechanism, initial position and parameter
changes. The movement of the gripping mechanism is smooth and follows
the defined trajectory.",
publisher = "University of Belgrade - Faculty of Mechanical Engineering",
journal = "FME Transactions",
title = "Fuzzy Controller Optimized by the African Vultures Algorithm for Trajectory Tracking of a Two–Link Gripping Mechanism",
pages = "501-491",
number = "3",
volume = "50",
doi = "10.5937/fme2203491J"
}

Jovanović, R., Bugarić, U., Vesović, M.,& Perišić, N.. (2022). Fuzzy Controller Optimized by the African Vultures Algorithm for Trajectory Tracking of a Two–Link Gripping Mechanism. in FME Transactions
University of Belgrade - Faculty of Mechanical Engineering., 50(3), 491-501.
https://doi.org/10.5937/fme2203491J

Jovanović R, Bugarić U, Vesović M, Perišić N. Fuzzy Controller Optimized by the African Vultures Algorithm for Trajectory Tracking of a Two–Link Gripping Mechanism. in FME Transactions. 2022;50(3):491-501.
doi:10.5937/fme2203491J .

Jovanović, Radiša, Bugarić, Uglješa, Vesović, Mitra , Perišić, Natalija, "Fuzzy Controller Optimized by the African Vultures Algorithm for Trajectory Tracking of a Two–Link Gripping Mechanism" in FME Transactions, 50, no. 3 (2022):491-501,
https://doi.org/10.5937/fme2203491J . .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Nedeljković, Dušan
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5278
AB  - U okviru ovog rada navode se rezultati istraživanja sprovedenih u okviru projekta MISSION4.0 pod nazivom Optimizacioni algoritmi za upravljanje i terminiranje kibernetsko fizičkih sistema u okviru Industrije 4.0 zasnovani na dubokom mašinskom učenju i inteligenciji roja, finansiranog od strane Fonda za nauku Republike Srbije u periodu od 2020-2022. godine. Prikazani rezultati odnose se na oblast sajber bezbednosti u kontinualnim sistemima upravljanja što predstavlja jedan od radnih paketa projekta MISSION4.0. U skladu sa tim, pravci istraživanja odnosili su se na razvoj algoritama za detekciju napada u industrijskim sistemima upravljanja sa centralizovanom i distribuiranom arhitekturom, kao i na primenu otvorene platforme za komunikaciju, u cilju bezbedne razmene podataka između uređaja različitih proizvođača. Pored toga, dobijeni rezultati i njihova integracija u predavanja i laboratorijske vežbe poslužili su kao osnova za edukaciju inženjera u oblastima kibernetsko fizičkih sistema, industrijskog interneta stvari i sajber bezbednosti.
PB  - University of Belgrade - Faculty of Mechanical Engineering
C3  - 43. JUPITER konferencija, 36. simpozijum „CIM u strategiji tehnološkog razvoja industrije prerade metala“, Zbornik radova / 43rd JUPITER Conference, Proceedings, Beograd, oktobar 2022
T1  - Sajber bezbednost u kontinualnim sistemima upravljanja – pregled rezultata u okviru projekta mission4.0
T1  - Cyber security in continuous-time controlled systems – overview of the results within the project of mission4.0
EP  - 1.16
SP  - 1.7
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5278
ER  - 

@conference{
author = "Jakovljević, Živana and Nedeljković, Dušan",
year = "2022",
abstract = "U okviru ovog rada navode se rezultati istraživanja sprovedenih u okviru projekta MISSION4.0 pod nazivom Optimizacioni algoritmi za upravljanje i terminiranje kibernetsko fizičkih sistema u okviru Industrije 4.0 zasnovani na dubokom mašinskom učenju i inteligenciji roja, finansiranog od strane Fonda za nauku Republike Srbije u periodu od 2020-2022. godine. Prikazani rezultati odnose se na oblast sajber bezbednosti u kontinualnim sistemima upravljanja što predstavlja jedan od radnih paketa projekta MISSION4.0. U skladu sa tim, pravci istraživanja odnosili su se na razvoj algoritama za detekciju napada u industrijskim sistemima upravljanja sa centralizovanom i distribuiranom arhitekturom, kao i na primenu otvorene platforme za komunikaciju, u cilju bezbedne razmene podataka između uređaja različitih proizvođača. Pored toga, dobijeni rezultati i njihova integracija u predavanja i laboratorijske vežbe poslužili su kao osnova za edukaciju inženjera u oblastima kibernetsko fizičkih sistema, industrijskog interneta stvari i sajber bezbednosti.",
publisher = "University of Belgrade - Faculty of Mechanical Engineering",
journal = "43. JUPITER konferencija, 36. simpozijum „CIM u strategiji tehnološkog razvoja industrije prerade metala“, Zbornik radova / 43rd JUPITER Conference, Proceedings, Beograd, oktobar 2022",
title = "Sajber bezbednost u kontinualnim sistemima upravljanja – pregled rezultata u okviru projekta mission4.0, Cyber security in continuous-time controlled systems – overview of the results within the project of mission4.0",
pages = "1.16-1.7",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5278"
}

Jakovljević, Ž.,& Nedeljković, D.. (2022). Sajber bezbednost u kontinualnim sistemima upravljanja – pregled rezultata u okviru projekta mission4.0. in 43. JUPITER konferencija, 36. simpozijum „CIM u strategiji tehnološkog razvoja industrije prerade metala“, Zbornik radova / 43rd JUPITER Conference, Proceedings, Beograd, oktobar 2022
University of Belgrade - Faculty of Mechanical Engineering., 1.7-1.16.
https://hdl.handle.net/21.15107/rcub_machinery_5278

Jakovljević Ž, Nedeljković D. Sajber bezbednost u kontinualnim sistemima upravljanja – pregled rezultata u okviru projekta mission4.0. in 43. JUPITER konferencija, 36. simpozijum „CIM u strategiji tehnološkog razvoja industrije prerade metala“, Zbornik radova / 43rd JUPITER Conference, Proceedings, Beograd, oktobar 2022. 2022;:1.7-1.16.
https://hdl.handle.net/21.15107/rcub_machinery_5278 .

Jakovljević, Živana, Nedeljković, Dušan, "Sajber bezbednost u kontinualnim sistemima upravljanja – pregled rezultata u okviru projekta mission4.0" in 43. JUPITER konferencija, 36. simpozijum „CIM u strategiji tehnološkog razvoja industrije prerade metala“, Zbornik radova / 43rd JUPITER Conference, Proceedings, Beograd, oktobar 2022 (2022):1.7-1.16,
https://hdl.handle.net/21.15107/rcub_machinery_5278 .

TY  - CONF
AU  - Nedeljković, Dušan
AU  - Jakovljević, Živana
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5277
AB  - The advent of the Industry 4.0 paradigm that relies on the concepts of Cyber-Physical Systems (CPS) and the Industrial Internet of Things (IIoT) leads to the transition from centralized to distributed control. In this approach, interconnected smart devices (sensors, actuators, etc.) as the key enablers achieve system control through coordinated work. Introduction of IIoT leads to ubiquitous communication between smart devices, thus opening up a vast area for potential malicious threats and attacks which can cause serious consequences, take to system dysfunction or even endanger human lives. Therefore, security mechanisms have to be developed to provide timely detection of different cyber-attacks and to keep the system safe and protected. Since industrial processes are often very complex and their analytical model is very difficult to determine, deep learning based methods for cyber-security mechanisms development are imposed as a technique of choice. Successful employment of data-driven solutions, particularly based on deep learning approaches usually requires a big amount of data. However, due to various limitations in the acquisition of data from the real process, its availability is still a major challenge. For instance, the Industry 4.0 factory implies frequent reconfiguration which reduces the time intervals available for experimental procedures such as data acquisition. One of the ways to deal with this issue is called data augmentation. In this paper, we apply data augmentation in the design of cyber-attack detection methods in Industrial Control Systems (ICS). In particular, we explore the possibilities for utilization of Generative Adversarial Networks (GAN) to generate the necessary amount of data for deep learning based modeling sing a relatively small number of available samples on input.
PB  - ETRAN Society, Belgrade, Academic Mind, Belgrade
C3  - 9th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2022), Proceedings, Novi Pazar, June 2022, ROI1.4
T1  - Gan-based data augmentation in the design of Cyber-attack detection methods
SP  - ROI1.4
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5277
ER  - 

@conference{
author = "Nedeljković, Dušan and Jakovljević, Živana",
year = "2022",
abstract = "The advent of the Industry 4.0 paradigm that relies on the concepts of Cyber-Physical Systems (CPS) and the Industrial Internet of Things (IIoT) leads to the transition from centralized to distributed control. In this approach, interconnected smart devices (sensors, actuators, etc.) as the key enablers achieve system control through coordinated work. Introduction of IIoT leads to ubiquitous communication between smart devices, thus opening up a vast area for potential malicious threats and attacks which can cause serious consequences, take to system dysfunction or even endanger human lives. Therefore, security mechanisms have to be developed to provide timely detection of different cyber-attacks and to keep the system safe and protected. Since industrial processes are often very complex and their analytical model is very difficult to determine, deep learning based methods for cyber-security mechanisms development are imposed as a technique of choice. Successful employment of data-driven solutions, particularly based on deep learning approaches usually requires a big amount of data. However, due to various limitations in the acquisition of data from the real process, its availability is still a major challenge. For instance, the Industry 4.0 factory implies frequent reconfiguration which reduces the time intervals available for experimental procedures such as data acquisition. One of the ways to deal with this issue is called data augmentation. In this paper, we apply data augmentation in the design of cyber-attack detection methods in Industrial Control Systems (ICS). In particular, we explore the possibilities for utilization of Generative Adversarial Networks (GAN) to generate the necessary amount of data for deep learning based modeling sing a relatively small number of available samples on input.",
publisher = "ETRAN Society, Belgrade, Academic Mind, Belgrade",
journal = "9th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2022), Proceedings, Novi Pazar, June 2022, ROI1.4",
title = "Gan-based data augmentation in the design of Cyber-attack detection methods",
pages = "ROI1.4",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5277"
}

Nedeljković, D.,& Jakovljević, Ž.. (2022). Gan-based data augmentation in the design of Cyber-attack detection methods. in 9th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2022), Proceedings, Novi Pazar, June 2022, ROI1.4
ETRAN Society, Belgrade, Academic Mind, Belgrade., ROI1.4.
https://hdl.handle.net/21.15107/rcub_machinery_5277

Nedeljković D, Jakovljević Ž. Gan-based data augmentation in the design of Cyber-attack detection methods. in 9th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2022), Proceedings, Novi Pazar, June 2022, ROI1.4. 2022;:ROI1.4.
https://hdl.handle.net/21.15107/rcub_machinery_5277 .

Nedeljković, Dušan, Jakovljević, Živana, "Gan-based data augmentation in the design of Cyber-attack detection methods" in 9th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN 2022), Proceedings, Novi Pazar, June 2022, ROI1.4 (2022):ROI1.4,
https://hdl.handle.net/21.15107/rcub_machinery_5277 .

TY  - CONF
AU  - Zarić, Vladimir
AU  - Perišić, Natalija
AU  - Jovanović, Radiša
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4510
AB  - This paper deals with liquid level control as one of the frequent problems in industry. Several classical methods for tuning a PID like controller were applied. Furthermore, parameters for the controller were optimized using grey wolf optimizer. In addition to the classical controller, fuzzy PID like controller has also been designed and optimized using the same optimization algorithm. Experimental results obtained on the tank system are provided.
PB  - Kraljevo: Faculty of Mechanical and Civil Engineering
C3  - The Tennth International Triennial Conference Heavy Machinery HM 2021: Proceedings, Vrnjačka Banja, June 23-25
T1  - Control of a Liquid Level System Based on Classical and Fuzzy PID Like Controller Using the Grey Wolf Optimization Algorithm
EP  - C30
SP  - C23
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4510
ER  - 

@conference{
author = "Zarić, Vladimir and Perišić, Natalija and Jovanović, Radiša",
year = "2021",
abstract = "This paper deals with liquid level control as one of the frequent problems in industry. Several classical methods for tuning a PID like controller were applied. Furthermore, parameters for the controller were optimized using grey wolf optimizer. In addition to the classical controller, fuzzy PID like controller has also been designed and optimized using the same optimization algorithm. Experimental results obtained on the tank system are provided.",
publisher = "Kraljevo: Faculty of Mechanical and Civil Engineering",
journal = "The Tennth International Triennial Conference Heavy Machinery HM 2021: Proceedings, Vrnjačka Banja, June 23-25",
title = "Control of a Liquid Level System Based on Classical and Fuzzy PID Like Controller Using the Grey Wolf Optimization Algorithm",
pages = "C30-C23",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4510"
}

Zarić, V., Perišić, N.,& Jovanović, R.. (2021). Control of a Liquid Level System Based on Classical and Fuzzy PID Like Controller Using the Grey Wolf Optimization Algorithm. in The Tennth International Triennial Conference Heavy Machinery HM 2021: Proceedings, Vrnjačka Banja, June 23-25
Kraljevo: Faculty of Mechanical and Civil Engineering., C23-C30.
https://hdl.handle.net/21.15107/rcub_machinery_4510

Zarić V, Perišić N, Jovanović R. Control of a Liquid Level System Based on Classical and Fuzzy PID Like Controller Using the Grey Wolf Optimization Algorithm. in The Tennth International Triennial Conference Heavy Machinery HM 2021: Proceedings, Vrnjačka Banja, June 23-25. 2021;:C23-C30.
https://hdl.handle.net/21.15107/rcub_machinery_4510 .

Zarić, Vladimir, Perišić, Natalija, Jovanović, Radiša, "Control of a Liquid Level System Based on Classical and Fuzzy PID Like Controller Using the Grey Wolf Optimization Algorithm" in The Tennth International Triennial Conference Heavy Machinery HM 2021: Proceedings, Vrnjačka Banja, June 23-25 (2021):C23-C30,
https://hdl.handle.net/21.15107/rcub_machinery_4510 .

TY  - JOUR
AU  - Gruyitch, Lyubomir
AU  - Bučevac, Zoran M.
AU  - Jovanović, Radiša
AU  - Zarić, Vladimir
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3516
AB  - Dynamic systems operate under the simultaneous influence of both the initial conditions and the input vector. There is neither physical nor mathematical justification for ignoring the initial conditions, e.g., in the control optimisation. This paper gives a response to the following question: Is a set of controller parameters which is optimal for the operation of a control system under zero initial conditions also optimal for its operation under non-zero initial conditions? The paper presents a new approach to the design of a classical proportional-differencesum (PDS) controller for a plant in a closed loop control system. The system relative stability with respect to a desired damping coefficient is accomplished. The minimal value of the performance index in the form of the sum of squared errors is the optimality criterion. Unlike the classical approach, the output error used in the performance index is influenced by all actions performed on the system at the same time.
PB  - Univ Zagreb Fac Mechanical Engineering & Naval Architecture, Zagreb
T2  - Transactions of Famena
T1  - Discrete-time system conditional optimisation in the parameter space via the full transfer function matrix
EP  - 62
IS  - 3
SP  - 45
VL  - 45
DO  - 10.21278/TOF.453014220
ER  - 

@article{
author = "Gruyitch, Lyubomir and Bučevac, Zoran M. and Jovanović, Radiša and Zarić, Vladimir",
year = "2021",
abstract = "Dynamic systems operate under the simultaneous influence of both the initial conditions and the input vector. There is neither physical nor mathematical justification for ignoring the initial conditions, e.g., in the control optimisation. This paper gives a response to the following question: Is a set of controller parameters which is optimal for the operation of a control system under zero initial conditions also optimal for its operation under non-zero initial conditions? The paper presents a new approach to the design of a classical proportional-differencesum (PDS) controller for a plant in a closed loop control system. The system relative stability with respect to a desired damping coefficient is accomplished. The minimal value of the performance index in the form of the sum of squared errors is the optimality criterion. Unlike the classical approach, the output error used in the performance index is influenced by all actions performed on the system at the same time.",
publisher = "Univ Zagreb Fac Mechanical Engineering & Naval Architecture, Zagreb",
journal = "Transactions of Famena",
title = "Discrete-time system conditional optimisation in the parameter space via the full transfer function matrix",
pages = "62-45",
number = "3",
volume = "45",
doi = "10.21278/TOF.453014220"
}

Gruyitch, L., Bučevac, Z. M., Jovanović, R.,& Zarić, V.. (2021). Discrete-time system conditional optimisation in the parameter space via the full transfer function matrix. in Transactions of Famena
Univ Zagreb Fac Mechanical Engineering & Naval Architecture, Zagreb., 45(3), 45-62.
https://doi.org/10.21278/TOF.453014220

Gruyitch L, Bučevac ZM, Jovanović R, Zarić V. Discrete-time system conditional optimisation in the parameter space via the full transfer function matrix. in Transactions of Famena. 2021;45(3):45-62.
doi:10.21278/TOF.453014220 .

Gruyitch, Lyubomir, Bučevac, Zoran M., Jovanović, Radiša, Zarić, Vladimir, "Discrete-time system conditional optimisation in the parameter space via the full transfer function matrix" in Transactions of Famena, 45, no. 3 (2021):45-62,
https://doi.org/10.21278/TOF.453014220 . .

TY  - THES
AU  - Stanković, Ivana
PY  - 2021
UR  - http://eteze.bg.ac.rs/application/showtheses?thesesId=8200
UR  - https://fedorabg.bg.ac.rs/fedora/get/o:23885/bdef:Content/download
UR  - http://vbs.rs/scripts/cobiss?command=DISPLAY&base=70036&RID=39955977
UR  - https://nardus.mpn.gov.rs/handle/123456789/18382
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/79
AB  - Ispitivanje uticaja svetlosti, kako prirodne tako i veštačke, od izuzetne je važnosti sa aspekta zdravlja očnog aparata i funkcionisanja ljudskog organizma generalno. Očne strukture poseduju različit stepen osetljivosti na dejstvo elektromagnetnog zračenja, tako da neke talasne dužine mogu prouzrokovati fotohemijska i fototermalna oštećenja. Zračenje u domenu ultraljubičastog (UV) i visoko-energetskog plavog svetla predstavlja izuzetnu pretnju očnim tkivima, uz istovremen uticaj i na moždane funkcije. Istraživanje novih materijala koji će biti u mogućnosti da filtriraju i potpuno eliminišu ili transformišu štetne talasne dužine zračenja je od savremenog javnog značaja. Novi optički materijali treba da poseduju sposobnost podešavanja i preciznog definisanja karakteristika talasnih dužina transmitovanog zračenja. Mnogi fotofizički i fotohemijski procesi upravo zavise od izbora talasne dužine tako da optički filteri, sa različitim transmisionim karakteristikama, omogućavaju fotostimulaciju istih i kao takvi potomažu razvoju novih fotonskih uređaja, fototerapijskih aparata i zaštitinih pomagala. Uočeno je da prilikom zatamnjenja optičkih pomagala, stavljanja blokatora za UV i plavu svetlost, nisu zadovoljeni kriterijumi osetljivosti oka pa dolazi do pojave neželjenih efekata, čije dejstvo izaziva naprezanje očnih struktura, a zatim i njihovo oštećenje. Saglasno tome, osnovni cilj ove doktorske disertacije je iznalaženje optičkog pomagala koje će sprečiti štetan uticaj UV i visoko-energetskog plavog svetla, uz transformaciju upadnog spektara svetlosti tako da bude što bliži spektru osetljivosti oka. U svrhu realizacije postavljenih ciljeva istraživanja, za izradu optičkog pomagala korišćeni su nanokompozitni materijali na bazi polimera (poli (metil metakrilata), PMMA) i nanomaterijala, fulerena (C60). Nanokompozitni materijali izrađeni su sa četiri koncentracije nanomaterijala (0.025mas%, 0.050mas%, 0.075mas% i 0.100mas%.). Za ispitivanje optičkih karakteristika nanokompozitnih materijala korišćeni su UV/VIS spektrofotometar (ILT350 Spectroradiometer, International Light Technologies, SAD), UV/VIS/NIR spektrometri (Lambda 950, Perkin Elmer, Italija i C10082CA, Mini-spectrometer, Hamamatsu, Japan) i FTIR mikrospektroskopski sistem (Spotlight 400 FT-IR Imaging System, Perkin Elmer, Italija). Za nanokarakterizaciju novih materijala korišćen je uređaj za mikroskopiju atomskih i magnetnih sila (JSPM 5200, JEOL, Japan). Istraživanjem su definisane razlike difuzne svetlosti koja ulazi u sistem optičkog pomagala i izlazne svetlosti iz optičkog pomagala. Multifaktorska analiza snimljenih karakteristika nanokompozitnih materijala za optička pomagala, spektroskopskim i nanotehnološkim metodama i tehnikama, ukazuje na značaj koncentracije molekula S60 u nanokompozitnom materijalu, odnosno uticaju njegove koncentracije na optička i strukturna svojstva novodobijenog materijala. Eksperimentalno je utvrđeno koja od navedene četiri koncentracije najviše pogoduje izradi optičkog pomagala. Probna sočiva, sa adekvatnom koncentracijom nanomaterijala, testirana su u okviru preliminarne oftalmološke studije, u dve oftalmološke ordinacije, Laserfocus i Macula, iz Beograda.
PB  - Univerzitet u Beogradu, Mašinski fakultet
T1  - Karakterizacija nanokompozitnih materijala za optička pomagala
T1  - Characterization of nanocomposite materials for optical aids
UR  - https://hdl.handle.net/21.15107/rcub_nardus_18382
ER  - 

@phdthesis{
author = "Stanković, Ivana",
year = "2021",
abstract = "Ispitivanje uticaja svetlosti, kako prirodne tako i veštačke, od izuzetne je važnosti sa aspekta zdravlja očnog aparata i funkcionisanja ljudskog organizma generalno. Očne strukture poseduju različit stepen osetljivosti na dejstvo elektromagnetnog zračenja, tako da neke talasne dužine mogu prouzrokovati fotohemijska i fototermalna oštećenja. Zračenje u domenu ultraljubičastog (UV) i visoko-energetskog plavog svetla predstavlja izuzetnu pretnju očnim tkivima, uz istovremen uticaj i na moždane funkcije. Istraživanje novih materijala koji će biti u mogućnosti da filtriraju i potpuno eliminišu ili transformišu štetne talasne dužine zračenja je od savremenog javnog značaja. Novi optički materijali treba da poseduju sposobnost podešavanja i preciznog definisanja karakteristika talasnih dužina transmitovanog zračenja. Mnogi fotofizički i fotohemijski procesi upravo zavise od izbora talasne dužine tako da optički filteri, sa različitim transmisionim karakteristikama, omogućavaju fotostimulaciju istih i kao takvi potomažu razvoju novih fotonskih uređaja, fototerapijskih aparata i zaštitinih pomagala. Uočeno je da prilikom zatamnjenja optičkih pomagala, stavljanja blokatora za UV i plavu svetlost, nisu zadovoljeni kriterijumi osetljivosti oka pa dolazi do pojave neželjenih efekata, čije dejstvo izaziva naprezanje očnih struktura, a zatim i njihovo oštećenje. Saglasno tome, osnovni cilj ove doktorske disertacije je iznalaženje optičkog pomagala koje će sprečiti štetan uticaj UV i visoko-energetskog plavog svetla, uz transformaciju upadnog spektara svetlosti tako da bude što bliži spektru osetljivosti oka. U svrhu realizacije postavljenih ciljeva istraživanja, za izradu optičkog pomagala korišćeni su nanokompozitni materijali na bazi polimera (poli (metil metakrilata), PMMA) i nanomaterijala, fulerena (C60). Nanokompozitni materijali izrađeni su sa četiri koncentracije nanomaterijala (0.025mas%, 0.050mas%, 0.075mas% i 0.100mas%.). Za ispitivanje optičkih karakteristika nanokompozitnih materijala korišćeni su UV/VIS spektrofotometar (ILT350 Spectroradiometer, International Light Technologies, SAD), UV/VIS/NIR spektrometri (Lambda 950, Perkin Elmer, Italija i C10082CA, Mini-spectrometer, Hamamatsu, Japan) i FTIR mikrospektroskopski sistem (Spotlight 400 FT-IR Imaging System, Perkin Elmer, Italija). Za nanokarakterizaciju novih materijala korišćen je uređaj za mikroskopiju atomskih i magnetnih sila (JSPM 5200, JEOL, Japan). Istraživanjem su definisane razlike difuzne svetlosti koja ulazi u sistem optičkog pomagala i izlazne svetlosti iz optičkog pomagala. Multifaktorska analiza snimljenih karakteristika nanokompozitnih materijala za optička pomagala, spektroskopskim i nanotehnološkim metodama i tehnikama, ukazuje na značaj koncentracije molekula S60 u nanokompozitnom materijalu, odnosno uticaju njegove koncentracije na optička i strukturna svojstva novodobijenog materijala. Eksperimentalno je utvrđeno koja od navedene četiri koncentracije najviše pogoduje izradi optičkog pomagala. Probna sočiva, sa adekvatnom koncentracijom nanomaterijala, testirana su u okviru preliminarne oftalmološke studije, u dve oftalmološke ordinacije, Laserfocus i Macula, iz Beograda.",
publisher = "Univerzitet u Beogradu, Mašinski fakultet",
title = "Karakterizacija nanokompozitnih materijala za optička pomagala, Characterization of nanocomposite materials for optical aids",
url = "https://hdl.handle.net/21.15107/rcub_nardus_18382"
}

Stanković, I.. (2021). Karakterizacija nanokompozitnih materijala za optička pomagala. 
Univerzitet u Beogradu, Mašinski fakultet..
https://hdl.handle.net/21.15107/rcub_nardus_18382

Stanković I. Karakterizacija nanokompozitnih materijala za optička pomagala. 2021;.
https://hdl.handle.net/21.15107/rcub_nardus_18382 .

Stanković, Ivana, "Karakterizacija nanokompozitnih materijala za optička pomagala" (2021),
https://hdl.handle.net/21.15107/rcub_nardus_18382 .

TY  - BOOK
AU  - Kalajdžić, Milisav
AU  - Tanović, Ljubodrag
AU  - Babić, Bojan
AU  - Glavonjić, Miloš
AU  - Miljković, Zoran
AU  - Puzović, Radovan
AU  - Kokotović, Branko
AU  - Popović, Mihajlo
AU  - Živanović, Saša
AU  - Tošić, Dragan
AU  - Vasić, Ivan
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4436
AB  - Priručnik iz tehnologije obrade rezanjem namenjen je inženjerima, a posebno studentima kao pomoć pri izradi projektnih i ispitnih zadataka iz predmeta Tehnologija mašinogradnje nekada (do 2008. godine) i danas Tehnologija mašinske obrade, kao i iz drugih uže stručnih predmeta koje slušaju studenti proizvodnog mašinstva na osnovnim i master akademskim studijama Mašinskog fakulteta Univerziteta u Beogradu.
U prvom delu priručnika dat je formalizovan koncept za projektovanje i izbor tehnologije obrade rezanjem metala, koji je ilustrovan odgovarajućim primerima, dok drugi deo sadrži bogat sistem podataka, koji se odnose na:
(i) mašinske materijale i materijale reznih alata,
(ii) sistem kvaliteta i tačnost obrade,
(iii) obradne sisteme,
(iv) sistem podataka koji obuhvata režime obrade i
(v) sistem podataka, koji se odnosi na funkcije obradljivosti.
Ovaj priručnik, u pogledu svog sadržaja, predstavlja ravnotežu između klasičnog pristupa sa pokušajem da se svaki proces determiniše, i savremenog pristupa koji maksimizira izlaze i pojednostavljuje primenu. S druge strane, očekuje se da se znatno pojednostavi rešavanje određenih složenih inženjerskih problema, posebno prilikom projektovanja tehnoloških procesa obrade metala rezanjem.
PB  - Mašinski fakultet Univerziteta u Beogradu
T2  - UNIVERZITET U BEOGRADU - MAŠINSKI FAKULTET (COBISS.SR-ID - 48397833)
T1  - Технологија обраде резањем : приручник
T1  - CUTTING TECHNOLOGY: handbook
EP  - 453
IS  - IX izdanje
SP  - 1
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4436
ER  - 

@book{
author = "Kalajdžić, Milisav and Tanović, Ljubodrag and Babić, Bojan and Glavonjić, Miloš and Miljković, Zoran and Puzović, Radovan and Kokotović, Branko and Popović, Mihajlo and Živanović, Saša and Tošić, Dragan and Vasić, Ivan",
year = "2021",
abstract = "Priručnik iz tehnologije obrade rezanjem namenjen je inženjerima, a posebno studentima kao pomoć pri izradi projektnih i ispitnih zadataka iz predmeta Tehnologija mašinogradnje nekada (do 2008. godine) i danas Tehnologija mašinske obrade, kao i iz drugih uže stručnih predmeta koje slušaju studenti proizvodnog mašinstva na osnovnim i master akademskim studijama Mašinskog fakulteta Univerziteta u Beogradu.
U prvom delu priručnika dat je formalizovan koncept za projektovanje i izbor tehnologije obrade rezanjem metala, koji je ilustrovan odgovarajućim primerima, dok drugi deo sadrži bogat sistem podataka, koji se odnose na:
(i) mašinske materijale i materijale reznih alata,
(ii) sistem kvaliteta i tačnost obrade,
(iii) obradne sisteme,
(iv) sistem podataka koji obuhvata režime obrade i
(v) sistem podataka, koji se odnosi na funkcije obradljivosti.
Ovaj priručnik, u pogledu svog sadržaja, predstavlja ravnotežu između klasičnog pristupa sa pokušajem da se svaki proces determiniše, i savremenog pristupa koji maksimizira izlaze i pojednostavljuje primenu. S druge strane, očekuje se da se znatno pojednostavi rešavanje određenih složenih inženjerskih problema, posebno prilikom projektovanja tehnoloških procesa obrade metala rezanjem.",
publisher = "Mašinski fakultet Univerziteta u Beogradu",
journal = "UNIVERZITET U BEOGRADU - MAŠINSKI FAKULTET (COBISS.SR-ID - 48397833)",
title = "Технологија обраде резањем : приручник, CUTTING TECHNOLOGY: handbook",
pages = "453-1",
number = "IX izdanje",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4436"
}

Kalajdžić, M., Tanović, L., Babić, B., Glavonjić, M., Miljković, Z., Puzović, R., Kokotović, B., Popović, M., Živanović, S., Tošić, D.,& Vasić, I.. (2021). Технологија обраде резањем : приручник. in UNIVERZITET U BEOGRADU - MAŠINSKI FAKULTET (COBISS.SR-ID - 48397833)
Mašinski fakultet Univerziteta u Beogradu.(IX izdanje), 1-453.
https://hdl.handle.net/21.15107/rcub_machinery_4436

Kalajdžić M, Tanović L, Babić B, Glavonjić M, Miljković Z, Puzović R, Kokotović B, Popović M, Živanović S, Tošić D, Vasić I. Технологија обраде резањем : приручник. in UNIVERZITET U BEOGRADU - MAŠINSKI FAKULTET (COBISS.SR-ID - 48397833). 2021;(IX izdanje):1-453.
https://hdl.handle.net/21.15107/rcub_machinery_4436 .

Kalajdžić, Milisav, Tanović, Ljubodrag, Babić, Bojan, Glavonjić, Miloš, Miljković, Zoran, Puzović, Radovan, Kokotović, Branko, Popović, Mihajlo, Živanović, Saša, Tošić, Dragan, Vasić, Ivan, "Технологија обраде резањем : приручник" in UNIVERZITET U BEOGRADU - MAŠINSKI FAKULTET (COBISS.SR-ID - 48397833), no. IX izdanje (2021):1-453,
https://hdl.handle.net/21.15107/rcub_machinery_4436 .

TY  - CONF
AU  - Nedeljković, Dušan
AU  - Stanojević, Stefan
AU  - Puzović, Radovan
AU  - Jakovljević, Živana
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5274
AB  - Kompletna digitalizacija svih proizvodnih procesa u okviru Industrije 4.0 i povezivanje realnog sveta i njegove kibernetske (virtuelne) reprezentacije u realnom vremenu zahteva neometani protok informacija između i unutar svih nivoa piramide automatizacije. Jedan od ograničavajućih faktora u tom kontekstu predstavlja razmena podataka između uređaja i softverskih sistema različitih proizvođača koji po pravilu za komunikaciju koriste namenski kreirane protokole. Rešenje ovog problema se pronalazi u postizanju interoperabilnosti kroz primenu OPC-UA (engl. Open Platform Communication - Unified Architecture) standarda. U okviru ovog rada sprovedena je integracija resursa zasnovanih na servo motorima i sistema za izvršavanje proizvodnje korišćenjem OPC-UA.
PB  - University of Novi Sad, Faculty of Technical Sciences, Department of Production Engineering
C3  - Proceedings of the International Scientific Conference ETIKUM 2021, Novi Sad, 2021
T1  - Integracija proizvodnih resursa u sistem za izvršavanje proizvodnje korišćenjem opc-ua
EP  - 68
SP  - 65
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5274
ER  - 

@conference{
author = "Nedeljković, Dušan and Stanojević, Stefan and Puzović, Radovan and Jakovljević, Živana",
year = "2021",
abstract = "Kompletna digitalizacija svih proizvodnih procesa u okviru Industrije 4.0 i povezivanje realnog sveta i njegove kibernetske (virtuelne) reprezentacije u realnom vremenu zahteva neometani protok informacija između i unutar svih nivoa piramide automatizacije. Jedan od ograničavajućih faktora u tom kontekstu predstavlja razmena podataka između uređaja i softverskih sistema različitih proizvođača koji po pravilu za komunikaciju koriste namenski kreirane protokole. Rešenje ovog problema se pronalazi u postizanju interoperabilnosti kroz primenu OPC-UA (engl. Open Platform Communication - Unified Architecture) standarda. U okviru ovog rada sprovedena je integracija resursa zasnovanih na servo motorima i sistema za izvršavanje proizvodnje korišćenjem OPC-UA.",
publisher = "University of Novi Sad, Faculty of Technical Sciences, Department of Production Engineering",
journal = "Proceedings of the International Scientific Conference ETIKUM 2021, Novi Sad, 2021",
title = "Integracija proizvodnih resursa u sistem za izvršavanje proizvodnje korišćenjem opc-ua",
pages = "68-65",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5274"
}

Nedeljković, D., Stanojević, S., Puzović, R.,& Jakovljević, Ž.. (2021). Integracija proizvodnih resursa u sistem za izvršavanje proizvodnje korišćenjem opc-ua. in Proceedings of the International Scientific Conference ETIKUM 2021, Novi Sad, 2021
University of Novi Sad, Faculty of Technical Sciences, Department of Production Engineering., 65-68.
https://hdl.handle.net/21.15107/rcub_machinery_5274

Nedeljković D, Stanojević S, Puzović R, Jakovljević Ž. Integracija proizvodnih resursa u sistem za izvršavanje proizvodnje korišćenjem opc-ua. in Proceedings of the International Scientific Conference ETIKUM 2021, Novi Sad, 2021. 2021;:65-68.
https://hdl.handle.net/21.15107/rcub_machinery_5274 .

Nedeljković, Dušan, Stanojević, Stefan, Puzović, Radovan, Jakovljević, Živana, "Integracija proizvodnih resursa u sistem za izvršavanje proizvodnje korišćenjem opc-ua" in Proceedings of the International Scientific Conference ETIKUM 2021, Novi Sad, 2021 (2021):65-68,
https://hdl.handle.net/21.15107/rcub_machinery_5274 .

TY  - CONF
AU  - Nedeljković, Dušan
AU  - Jakovljević, Živana
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5276
AB  - The emergence of the Industry 4.0 concept leads to crucial changes in manufacturing by building advanced industrial systems and applications based on Cyber-Physical Systems (CPS), as the core of this approach. Using CPS, manufacturing assets are designed in the form of systems of systems through interconnection of smart devices with integrated computation and communication capabilities. System control logic is distributed over a large number of resources, and its performance is achieved through their coordinated work and ubiquitous communication raising the issue of cyber-attacks by malicious adversaries. Since cybersecurity within industrial control systems is safety related, it is necessary to timely detect cyber-attacks on industrial assets; for these purposes a number of different approaches have been developed. As a technique of choice, deep learning (DL) based methods emerge, providing good online performances. In this work, we focus on the implementation of a DL based cyber-attack detection algorithm on an electro-pneumatic positioning system containing smart sensor and smart actuator. In particular, we employ cyber-attack detection procedure based on 1D Convolutional Neural Network (CNN) at the local controller of the smart actuator. The implemented algorithm can successfully detect cyber-attacks in real-time, as will be experimentally demonstrated.
PB  - Faculty of Technical Sciences, Department of Production Engineering, Novi Sad
C3  - Proceedings of the 14th International Scientific Conference MMA 2021 - Flexible Technologies, Novi Sad, september 2021
T1  - Implementation of cnn based algorithm for cyber-attacks detection on a real-world control system
EP  - 122
SP  - 119
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5276
ER  - 

@conference{
author = "Nedeljković, Dušan and Jakovljević, Živana",
year = "2021",
abstract = "The emergence of the Industry 4.0 concept leads to crucial changes in manufacturing by building advanced industrial systems and applications based on Cyber-Physical Systems (CPS), as the core of this approach. Using CPS, manufacturing assets are designed in the form of systems of systems through interconnection of smart devices with integrated computation and communication capabilities. System control logic is distributed over a large number of resources, and its performance is achieved through their coordinated work and ubiquitous communication raising the issue of cyber-attacks by malicious adversaries. Since cybersecurity within industrial control systems is safety related, it is necessary to timely detect cyber-attacks on industrial assets; for these purposes a number of different approaches have been developed. As a technique of choice, deep learning (DL) based methods emerge, providing good online performances. In this work, we focus on the implementation of a DL based cyber-attack detection algorithm on an electro-pneumatic positioning system containing smart sensor and smart actuator. In particular, we employ cyber-attack detection procedure based on 1D Convolutional Neural Network (CNN) at the local controller of the smart actuator. The implemented algorithm can successfully detect cyber-attacks in real-time, as will be experimentally demonstrated.",
publisher = "Faculty of Technical Sciences, Department of Production Engineering, Novi Sad",
journal = "Proceedings of the 14th International Scientific Conference MMA 2021 - Flexible Technologies, Novi Sad, september 2021",
title = "Implementation of cnn based algorithm for cyber-attacks detection on a real-world control system",
pages = "122-119",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5276"
}

Nedeljković, D.,& Jakovljević, Ž.. (2021). Implementation of cnn based algorithm for cyber-attacks detection on a real-world control system. in Proceedings of the 14th International Scientific Conference MMA 2021 - Flexible Technologies, Novi Sad, september 2021
Faculty of Technical Sciences, Department of Production Engineering, Novi Sad., 119-122.
https://hdl.handle.net/21.15107/rcub_machinery_5276

Nedeljković D, Jakovljević Ž. Implementation of cnn based algorithm for cyber-attacks detection on a real-world control system. in Proceedings of the 14th International Scientific Conference MMA 2021 - Flexible Technologies, Novi Sad, september 2021. 2021;:119-122.
https://hdl.handle.net/21.15107/rcub_machinery_5276 .

Nedeljković, Dušan, Jakovljević, Živana, "Implementation of cnn based algorithm for cyber-attacks detection on a real-world control system" in Proceedings of the 14th International Scientific Conference MMA 2021 - Flexible Technologies, Novi Sad, september 2021 (2021):119-122,
https://hdl.handle.net/21.15107/rcub_machinery_5276 .

TY  - BOOK
AU  - Miljković, Zoran
AU  - Petrović, Milica
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4437
AB  - Овај основни уџбеник обухвата вишедеценијска искуства аутора остварена како кроз реализацију докторских дисертација, магистарских и мастер теза, као и при реализацији активности научно-истраживачких пројеката у домену развоја интелигентних технолошких система, тако и током образовног процеса и рада са бројним студентима на обавезним
предметима мастер академских студија Катедре за производно машинство под називом Интелигентни технолошки системи, Индустријски роботи и Методе одлучивања, а од 2020. године и на новоуспостављеном Студијском програму мастер академских студија Индустрија 4.0, у оквиру обавезних предмета Роботика и вештачка интелигенција, Машинско учење интелигентних роботских система и изборног предмета Терминирање технолошких система и процеса.
У овом капиталном уџбенику, поред детаљно обрађених наставних целина и брижљиво одабраних примера за набројане предмете, дате су и одговарајуће корисне дискусије аутора у домену производно оријентисаних напредних технологија, роботике и вештачке интелигенције, као и биолошки инспирисаних алгоритама оптимизације.
 Аутори очекују да, осим студентима, ова књига може корисно послужити мастер, односно дипломираним машинским инжењерима, а посебно докторандима који се баве истраживањем, развојем и увођењем интелигентних технолошких система и концепта Индустрија 4.0 у савремене производно оријентисане тзв. дигиталне фабрике.
PB  - Mašinski fakultet Univerziteta u Beogradu
T1  - ИНТЕЛИГЕНТНИ ТЕХНОЛОШКИ СИСТЕМИ - са изводима из роботике и вештачке интелигенције
T1  - INTELLIGENT MANUFACTURING SYSTEMS – with robotics and artificial intelligence backgrounds
EP  - 409
IS  - I izdanje
SP  - 1
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4437
ER  - 

@book{
author = "Miljković, Zoran and Petrović, Milica",
year = "2021",
abstract = "Овај основни уџбеник обухвата вишедеценијска искуства аутора остварена како кроз реализацију докторских дисертација, магистарских и мастер теза, као и при реализацији активности научно-истраживачких пројеката у домену развоја интелигентних технолошких система, тако и током образовног процеса и рада са бројним студентима на обавезним
предметима мастер академских студија Катедре за производно машинство под називом Интелигентни технолошки системи, Индустријски роботи и Методе одлучивања, а од 2020. године и на новоуспостављеном Студијском програму мастер академских студија Индустрија 4.0, у оквиру обавезних предмета Роботика и вештачка интелигенција, Машинско учење интелигентних роботских система и изборног предмета Терминирање технолошких система и процеса.
У овом капиталном уџбенику, поред детаљно обрађених наставних целина и брижљиво одабраних примера за набројане предмете, дате су и одговарајуће корисне дискусије аутора у домену производно оријентисаних напредних технологија, роботике и вештачке интелигенције, као и биолошки инспирисаних алгоритама оптимизације.
 Аутори очекују да, осим студентима, ова књига може корисно послужити мастер, односно дипломираним машинским инжењерима, а посебно докторандима који се баве истраживањем, развојем и увођењем интелигентних технолошких система и концепта Индустрија 4.0 у савремене производно оријентисане тзв. дигиталне фабрике.",
publisher = "Mašinski fakultet Univerziteta u Beogradu",
title = "ИНТЕЛИГЕНТНИ ТЕХНОЛОШКИ СИСТЕМИ - са изводима из роботике и вештачке интелигенције, INTELLIGENT MANUFACTURING SYSTEMS – with robotics and artificial intelligence backgrounds",
pages = "409-1",
number = "I izdanje",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4437"
}

Miljković, Z.,& Petrović, M.. (2021). ИНТЕЛИГЕНТНИ ТЕХНОЛОШКИ СИСТЕМИ - са изводима из роботике и вештачке интелигенције. 
Mašinski fakultet Univerziteta u Beogradu.(I izdanje), 1-409.
https://hdl.handle.net/21.15107/rcub_machinery_4437

Miljković Z, Petrović M. ИНТЕЛИГЕНТНИ ТЕХНОЛОШКИ СИСТЕМИ - са изводима из роботике и вештачке интелигенције. 2021;(I izdanje):1-409.
https://hdl.handle.net/21.15107/rcub_machinery_4437 .

Miljković, Zoran, Petrović, Milica, "ИНТЕЛИГЕНТНИ ТЕХНОЛОШКИ СИСТЕМИ - са изводима из роботике и вештачке интелигенције", no. I izdanje (2021):1-409,
https://hdl.handle.net/21.15107/rcub_machinery_4437 .

TY  - JOUR
AU  - Jakovljević, Živana
AU  - Lesi, Vuk
AU  - Pajić, Miroslav
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3622
AB  - Industrial Internet of Things (IIoT) represents a backbone of modern reconfigurable manufacturing systems (RMS), which enable manufacturing of a high product variety through rapid and easy reconfiguration of manufacturing equipment. In IIoT-enabled RMS, modular equipment is built from smart devices, each performing its own tasks, whereas the global functioning is achieved through their networking and intensive communication. Although device communication contributes to the system reconfigurability, it also opens up new security challenges due to potential vulnerability of communication links. In this article, we present security analysis for a major part of RMS in which manufacturing equipment is sequentially controlled and can be modeled as discrete event systems (DES). Control distribution within DES implies communication of certain events between smart modules. Specifically, in this work, we focus on attacks on communication of these events. In particular, we develop a method for modeling such attacks, including event insertion and removal attacks, in distributed sequential control; the method is based on the supervisory control theory framework. We show how the modeled attacks can be detected and provide a method for identification of communication links that require protection to avoid catastrophic damage of the system. Finally, we illustrate and experimentally validate applicability of our methodology on a real-world industrial case study with reconfigurable manufacturing equipment.
PB  - Ieee-Inst Electrical Electronics Engineers Inc, Piscataway
T2  - Ieee Transactions on Industrial Informatics
T1  - Attacks on Distributed Sequential Control in Manufacturing Automation
EP  - 786
IS  - 2
SP  - 775
VL  - 17
DO  - 10.1109/TII.2020.2987629
ER  - 

@article{
author = "Jakovljević, Živana and Lesi, Vuk and Pajić, Miroslav",
year = "2021",
abstract = "Industrial Internet of Things (IIoT) represents a backbone of modern reconfigurable manufacturing systems (RMS), which enable manufacturing of a high product variety through rapid and easy reconfiguration of manufacturing equipment. In IIoT-enabled RMS, modular equipment is built from smart devices, each performing its own tasks, whereas the global functioning is achieved through their networking and intensive communication. Although device communication contributes to the system reconfigurability, it also opens up new security challenges due to potential vulnerability of communication links. In this article, we present security analysis for a major part of RMS in which manufacturing equipment is sequentially controlled and can be modeled as discrete event systems (DES). Control distribution within DES implies communication of certain events between smart modules. Specifically, in this work, we focus on attacks on communication of these events. In particular, we develop a method for modeling such attacks, including event insertion and removal attacks, in distributed sequential control; the method is based on the supervisory control theory framework. We show how the modeled attacks can be detected and provide a method for identification of communication links that require protection to avoid catastrophic damage of the system. Finally, we illustrate and experimentally validate applicability of our methodology on a real-world industrial case study with reconfigurable manufacturing equipment.",
publisher = "Ieee-Inst Electrical Electronics Engineers Inc, Piscataway",
journal = "Ieee Transactions on Industrial Informatics",
title = "Attacks on Distributed Sequential Control in Manufacturing Automation",
pages = "786-775",
number = "2",
volume = "17",
doi = "10.1109/TII.2020.2987629"
}

Jakovljević, Ž., Lesi, V.,& Pajić, M.. (2021). Attacks on Distributed Sequential Control in Manufacturing Automation. in Ieee Transactions on Industrial Informatics
Ieee-Inst Electrical Electronics Engineers Inc, Piscataway., 17(2), 775-786.
https://doi.org/10.1109/TII.2020.2987629

Jakovljević Ž, Lesi V, Pajić M. Attacks on Distributed Sequential Control in Manufacturing Automation. in Ieee Transactions on Industrial Informatics. 2021;17(2):775-786.
doi:10.1109/TII.2020.2987629 .

Jakovljević, Živana, Lesi, Vuk, Pajić, Miroslav, "Attacks on Distributed Sequential Control in Manufacturing Automation" in Ieee Transactions on Industrial Informatics, 17, no. 2 (2021):775-786,
https://doi.org/10.1109/TII.2020.2987629 . .