Study Of Optimizing Parameters Of Improved Fuzzy Controllers By Genetic Algorithm

Fuzzy controllers can depend on expert experience to control complex system.The characteristic of the fuzzy controller makes its use more and more widely.This paper studied the fuzzy controller, in view of the lack of intelligent fuzzy controller itself and the poor ability to eliminate the steady-state error of shortcomings, puts forward the improved fuzzy controllers.By increasing the adjustment factor and integral, makes the dynamic performance and steady-state performance of the fuzzy controller is greatly increased.Aiming at the problem of difficult adjustment fuzzy controller parameters, put forward the method of using genetic algorithm to optimize fuzzy controllers parameters, the adaptive fuzzy controllers is greatly improved.This paper used Matlab to simulate improved fuzzy controllers and compared the improved fuzzy controller and the performance of the conventional fuzzy controller.At the same time compared improved fuzzy controller and PID controller under the different condition. The experimental results show that the improved fuzzy controls performance is more superior.The improved fuzzy controller used in DC motor speed control system to verify the performance of the improved fuzzy controller.First established the mathematical model of the DC motor,to verify the effectiveness of the improved fuzzy controller of DC speed regulation system.Finally, built the double closed loop control system based on improved fuzzy controller, the experimental results show the good control effect.