Open AccessIdentification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimization algorithm
Author(s) -
Radiša Jovanović,
Vladimir Zarić
Publication year - 2022
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci210825324j
Subject(s) - control theory (sociology) , fuzzy logic , fuzzy control system , computer science , controller (irrigation) , compensation (psychology) , process (computing) , flow (mathematics) , mathematical optimization , control (management) , mathematics , artificial intelligence , psychology , geometry , psychoanalysis , agronomy , biology , operating system
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.