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

fYear

2014

fDate

8-10 Aug. 2014

Firstpage

2610

Lastpage

2613

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese

Conference_Location

Yantai

Print_ISBN

978-1-4799-4700-3

Type

conf

DOI

10.1109/CGNCC.2014.7007579

Filename

7007579