Title :
An optimal fuzzy PID controller
Author :
Tang, K.S. ; Man, Kim Fung ; Chen, Guanrong ; Kwong, Sam
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, China
fDate :
8/1/2001 12:00:00 AM
Abstract :
This paper introduces an optimal fuzzy proportional-integral-derivative (PID) controller. The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear structure of the proportional, integral, and derivative parts but has constant coefficient yet self-tuned control gains. Fuzzy logic is employed only for the design; the resulting controller does not need to execute any fuzzy rule base, and is actually a conventional PID controller with analytical formulae. The main improvement is in endowing the classical controller with a certain adaptive control capability. The constant PID control gains are optimized by using the multiobjective genetic algorithm (MOGA), thereby yielding an optimal fuzzy PID controller. Computer simulations are shown to demonstrate its improvement over the fuzzy PID controller without MOGA optimization
Keywords :
adaptive control; control system analysis computing; control system synthesis; discrete time systems; fuzzy control; genetic algorithms; optimal control; three-term control; adaptive control capability; computer simulation; constant PID control gains; control simulation; discrete-time controller; fuzzy rule base; linear structure; multiobjective genetic algorithm; optimal fuzzy PID controller design; proportional-integral-derivative control; self-tuned control gains; Adaptive control; Computer simulation; Fuzzy control; Fuzzy logic; Genetic algorithms; Optimal control; PD control; Pi control; Proportional control; Three-term control;
Journal_Title :
Industrial Electronics, IEEE Transactions on