Title :
Recursive Least Square and Fuzzy Modelling Using Genetic Algorithm for Process Control Application
Author :
Rahman, Ribhan Zafira Abdul ; Yusof, Rubiyah ; Khalid, Marzuki
Author_Institution :
Dept. of Electr. & Electron., Univ. Putra Malaysia, Serdang
Abstract :
A technique for the modelling of nonlinear process control using recursive least square and Takagi-Sugeno fuzzy system with genetic algorithm topology is described. This paper discusses the identification of parameters of the fuzzy sets at the antecedent part and linear model at the consequent part of fuzzy model within an application to process control. The key issues of finding the best model of the process are described. Results show that fuzzy model with genetic algorithm gives minimum mean squared error compare with recursive least square
Keywords :
fuzzy control; fuzzy set theory; genetic algorithms; least mean squares methods; nonlinear control systems; process control; topology; Takagi-Sugeno fuzzy system; fuzzy sets; genetic algorithm topology; minimum mean squared error; nonlinear process control; recursive least square; Circuits; Fuzzy control; Fuzzy sets; Fuzzy systems; Genetic algorithms; Heat pumps; Heat transfer; Least squares methods; Process control; Water heating;
Conference_Titel :
Modelling & Simulation, 2007. AMS '07. First Asia International Conference on
Conference_Location :
Phuket
Print_ISBN :
0-7695-2845-7
DOI :
10.1109/AMS.2007.83
