A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications
Апстракт
The optimal parametrization and tuning of control systems are still an open issue, which was the pointed out within the invited lecture at the University of Niš - Faculty of Mechanical Engineering in December 2020, presented "on-line" during the COVID-19 pandemic crisis.
These issues were explained:
- State-of-the-art approaches were applied to systems with slow dynamics; requirements of precision and quality in the dynamic response are not very demanding; the influence of the hard nonlinearities (friction and backslash) on cascade controllers optimization has not been considered;
- Evolutionary meta-heuristic optimization methods were involved;
- Advantages of both Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) rely on easy programming and implementation, fast convergence speed and effective performance. These advantages motivated introduction of swarm intelligence based strategies to optimize the controller’ parameters of feed drive system influenced by hard n...onlinearities such as friction and backlash.
Some important conclusions were presented:
- Particle swarm optimization and Grey Wolf-based strategies are used for optimal tuning of a P-PI cascade control parameters for feed drive systems of machine tools;
- The main performance index - the minimization of the maximum position error, directly influenced by nonlinearities such as friction and backlash;
- The proposed strategies enable the minimization of the maximum peak of the trajectory error improving the performance of the cascade control system and decreasing significantly the negative influence on quality of manufactured parts;
- The experimental comparison demonstrated that the proposed strategy outperforms the Fine Tune method in terms of less maximum position error and better accuracy of the control system.
- Future research directions are: implementation of multi-objective swarm intelligence-based optimization algorithms for the optimal design of cascade control systems.
Кључне речи:
The optimal parametrization and tuning of control systems / Particle Swarm Optimization Algorithm (PSO) / Grey Wolf Optimization (GWO) algorithm / Optimal tuning of a P-PI cascade control parameters / Performance of the cascade control system / The Fine Tune method / Less maximum position error / Better accuracy of the control system / Multi-objective swarm intelligence-based optimization algorithmsИзвор:
University of Niš, Faculty of Mechanical Engineering, Niš, Serbia, 2020Издавач:
- University of Niš, Faculty of Mechanical Engineering
Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200105 (Универзитет у Београду, Машински факултет) (RS-MESTD-inst-2020-200105)
- MISSION4.0 - Deep Machine Learning and Swarm Intelligence-Based Optimization Algorithms for Control and Scheduling of Cyber-Physical Systems in Industry 4.0 (RS-ScienceFundRS-AI-6523109)
Напомена:
- This invited lecture was presented "on-line" at the University of Niš - Faculty of Mechanical Engineering, during the Covid-19 pandemic crisis, on 9th December, 2020.
Колекције
Институција/група
Mašinski fakultetTY - GEN AU - Miljković, Zoran AU - Petrović, Milica PY - 2020 UR - https://machinery.mas.bg.ac.rs/handle/123456789/6644 AB - The optimal parametrization and tuning of control systems are still an open issue, which was the pointed out within the invited lecture at the University of Niš - Faculty of Mechanical Engineering in December 2020, presented "on-line" during the COVID-19 pandemic crisis. These issues were explained: - State-of-the-art approaches were applied to systems with slow dynamics; requirements of precision and quality in the dynamic response are not very demanding; the influence of the hard nonlinearities (friction and backslash) on cascade controllers optimization has not been considered; - Evolutionary meta-heuristic optimization methods were involved; - Advantages of both Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) rely on easy programming and implementation, fast convergence speed and effective performance. These advantages motivated introduction of swarm intelligence based strategies to optimize the controller’ parameters of feed drive system influenced by hard nonlinearities such as friction and backlash. Some important conclusions were presented: - Particle swarm optimization and Grey Wolf-based strategies are used for optimal tuning of a P-PI cascade control parameters for feed drive systems of machine tools; - The main performance index - the minimization of the maximum position error, directly influenced by nonlinearities such as friction and backlash; - The proposed strategies enable the minimization of the maximum peak of the trajectory error improving the performance of the cascade control system and decreasing significantly the negative influence on quality of manufactured parts; - The experimental comparison demonstrated that the proposed strategy outperforms the Fine Tune method in terms of less maximum position error and better accuracy of the control system. - Future research directions are: implementation of multi-objective swarm intelligence-based optimization algorithms for the optimal design of cascade control systems. PB - University of Niš, Faculty of Mechanical Engineering T2 - University of Niš, Faculty of Mechanical Engineering, Niš, Serbia T1 - A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications UR - https://hdl.handle.net/21.15107/rcub_machinery_6644 ER -
@misc{ author = "Miljković, Zoran and Petrović, Milica", year = "2020", abstract = "The optimal parametrization and tuning of control systems are still an open issue, which was the pointed out within the invited lecture at the University of Niš - Faculty of Mechanical Engineering in December 2020, presented "on-line" during the COVID-19 pandemic crisis. These issues were explained: - State-of-the-art approaches were applied to systems with slow dynamics; requirements of precision and quality in the dynamic response are not very demanding; the influence of the hard nonlinearities (friction and backslash) on cascade controllers optimization has not been considered; - Evolutionary meta-heuristic optimization methods were involved; - Advantages of both Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) rely on easy programming and implementation, fast convergence speed and effective performance. These advantages motivated introduction of swarm intelligence based strategies to optimize the controller’ parameters of feed drive system influenced by hard nonlinearities such as friction and backlash. Some important conclusions were presented: - Particle swarm optimization and Grey Wolf-based strategies are used for optimal tuning of a P-PI cascade control parameters for feed drive systems of machine tools; - The main performance index - the minimization of the maximum position error, directly influenced by nonlinearities such as friction and backlash; - The proposed strategies enable the minimization of the maximum peak of the trajectory error improving the performance of the cascade control system and decreasing significantly the negative influence on quality of manufactured parts; - The experimental comparison demonstrated that the proposed strategy outperforms the Fine Tune method in terms of less maximum position error and better accuracy of the control system. - Future research directions are: implementation of multi-objective swarm intelligence-based optimization algorithms for the optimal design of cascade control systems.", publisher = "University of Niš, Faculty of Mechanical Engineering", journal = "University of Niš, Faculty of Mechanical Engineering, Niš, Serbia", title = "A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications", url = "https://hdl.handle.net/21.15107/rcub_machinery_6644" }
Miljković, Z.,& Petrović, M.. (2020). A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications. in University of Niš, Faculty of Mechanical Engineering, Niš, Serbia University of Niš, Faculty of Mechanical Engineering.. https://hdl.handle.net/21.15107/rcub_machinery_6644
Miljković Z, Petrović M. A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications. in University of Niš, Faculty of Mechanical Engineering, Niš, Serbia. 2020;. https://hdl.handle.net/21.15107/rcub_machinery_6644 .
Miljković, Zoran, Petrović, Milica, "A Survey of Swarm Intelligence-based Optimization Algorithms for Tuning of Cascade Control Systems: Concepts, Models and Applications" in University of Niš, Faculty of Mechanical Engineering, Niš, Serbia (2020), https://hdl.handle.net/21.15107/rcub_machinery_6644 .
Related items
Showing items related by title, author, creator and subject.
-
Višeciljna fazi optimizacija veličine i položaja piezoelektričnih aktuatora i senzora za upravljanje vibracijama bazirana na optimizaciji rojem čestica (deo 1: teorijski model) / Mul'ticelevaja faza optimizacii razmera i raspoloženija p'ezoëlektričeskih privodov i datčikov dlja upravlenija vibracijami na osnove optimizacii roja častic (čast' 1: teoretičeskaja model') / (francuski) Optimisation 'fuzzy' multi objective de la taille et de la location des actuaires piézoélectriques et des capteurs pour le contrôle des vibrations basée sur l'optimisation par essaim des particules (première partie: modèle théorétique)
Zorić, Nemanja; Simonović, Aleksandar; Stupar, Slobodan; Jovanović, Miroslav; Lukić, Nebojša S. (Vojnotehnički institut, Beograd, 2014) -
Active vibration control of smart composite plates using optimized self-tuning fuzzy logic controller with optimization of placement, sizing and orientation of PFRC actuators
Zorić, Nemanja; Tomović, Aleksandar; Obradović, Aleksandar; Radulović, Radoslav; Petrović, Goran R. (Academic Press Ltd- Elsevier Science Ltd, London, 2019) -
Active vibration control of smart composite plates using optimized self-tuning fuzzy logic controller with optimization of placement, sizing and orientation of PFRC actuators
Zorić, Nemanja; Tomović, Aleksandar; Obradović, Aleksandar; Radulović, Radoslav; Petrović, Goran R. (Academic Press Ltd- Elsevier Science Ltd, London, 2019)