A Servo Motor Drives Based On Hybrid Genetic Algorithm Fuzzy Neural Controller

Abstract

The nonlinearity and time varying characteristics of a servo Motor (SM) make it very difficult to be controlled. Althoughproportional-integral-derivative (PID) controller are widely used in this field but the complex mathematical model of ( SM ) makes the design procedure of any PID controller very tedious ,in which the time varying behavior of ( SM ) reduces the accuracy of any PID controller used. The use of Fuzzy Logic Controllers (FLC) in such control problem is widely used too, since Fuzzy Logic does not need any mathematical model and only uses linguistic rules that are based on human expert. However, still checking the parameters of fuzzy logic neural network controller (FLNNC) is a hard task for such a system specially the center and width of the used member ship functions. In this paper a Hybrid Genetic Based (FLNNC) is introduce to control the (SM). The Parameters measurements of (SM) has been implemented based on Genetic Algorithm (GA) tuned (FLNN) with a technique in which only transient speed measurementis required for identification of the parameters (SM).The GAFLNN controller was simulated by MATLAB Simulink using the technique of PID type based onFLNN technique and the scaling gains, fuzzy logic rules, membership function, and coefficients of neural networkare optimized by genetic algorithm technique. Simulated results show a significant improvement in settling time and rising time also reduces overshoot, IAE and ISE and with variations of external load disturbance.