Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimizer
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 co...mpared. The experimental results on a heat flow platform are presented to validate efficiency of the proposed method.
Keywords:
temperature control / Takagi-Sugeno / parallel distributed compensation / grey wolf optimization algorithm / fuzzy control / discrete-time systemsSource:
Thermal Science, 2022, 26, 3, 2275-2286Publisher:
- Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd
Funding / projects:
- Ministry of Science, Technological Development and Innovation of the Republic of Serbia, institutional funding - 200105 (University of Belgrade, Faculty of Mechanical Engineering) (RS-MESTD-inst-2020-200105)
- An innovative ecologically based approach to implementation of intelligent manufacturing systems for production of sheet metal parts (RS-MESTD-Technological Development (TD or TR)-35004)
- Development of Methodology for Improvement of Operational Performance, Reliability and Energy Efficiency of Machine Systems used in the Resource Industry (RS-MESTD-Technological Development (TD or TR)-35029)
DOI: 10.2298/TSCI210825324J
ISSN: 0354-9836
WoS: 000805859400021
Scopus: 2-s2.0-85131441594
Collections
Institution/Community
Mašinski fakultetTY - 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 . .