Title :
Optimal design for fuzzy controllers by genetic algorithms
Author :
Zhou, Yi-Sheng ; Lai, Lin-Ying
Author_Institution :
Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung Li, Taiwan
Abstract :
Fuzzy control has been applied to various industrial processes; however, its control rules and membership functions are usually obtained by trial and error. Proposed in this paper is an optimal design for membership functions and control rules simultaneously by a genetic algorithm (GA). GAs are search algorithms based on the mechanics of natural selection and natural genetics. They are easy to implement and efficient for multivariable optimization problems, such as fuzzy controller design. The simulation result shows that the fuzzy controller thus designed can achieve good performance merely by using a few fuzzy variables
Keywords :
control system analysis; control system synthesis; fuzzy control; genetic algorithms; optimal control; process control; control performance; control rules; control simulation; fuzzy optimal controller design; genetic algorithms; industrial processes; membership functions; multivariable optimization problems; natural genetics; natural selection; search algorithms; trial and error; Algorithm design and analysis; Automation; Control systems; Fuzzy control; Genetic algorithms; Industrial control; Nonlinear control systems; Optimal control; Process control; Transfer functions;
Journal_Title :
Industry Applications, IEEE Transactions on
