Title :
Optimization of fuzzy control rules based on differential evolution algorithm
Author :
Li Shuai ; Sun Wei
Author_Institution :
Sch. of Mechatron. Eng. & Autom., Shanghai Univ., Shanghai, China
Abstract :
The fuzzy control does not need accurate mathematics model, and has the feature of simple implementation and good control effect. But there isn´t a systematic design method, and it´s more difficult to adjust fuzzy rules because of the influence of subjective factors. To solve the problem, a method using improved differential evolution algorithm to optimize fuzzy control rules is presented in this paper. The optimization process is realized by using matlab procedure to the two-tank system and the simulation result suggests that, the control qualities of fuzzy controller, of which the control rules have been optimized, has been much improved.
Keywords :
evolutionary computation; fuzzy control; optimisation; Matlab procedure; fuzzy control rule optimization; fuzzy rule adjustment; improved differential evolution algorithm; optimization process; subjective factors; two-tank system; Fuzzy control; Heuristic algorithms; Niobium; Optimization; Sociology; Statistics; Vectors; Differential evolution; Fuzzy control rules; Optimization;
Conference_Titel :
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4799-4700-3
DOI :
10.1109/CGNCC.2014.7007579