An Improved genetic algorithm for the design of a fuzzy supervisory controller for a PH neutralization process

The purpose of this paper is to design a fuzzy supervisory PID controller using an improved genetic algorithm. The fuzzy controllers are widely used in the recent years due to their results in both tracking and perturbation rejection, however the most difficult step in designing a fuzzy controller is the fuzzyficaion stage where we have to determine the rules and the shape of membership functions. To overcome the problem an improved genetic algorithm is developed to determine the optimal rule and membership functions that are used in the supervisory controller to find Kp, Ki and Kd of the PID controller. The considered type of membership functions are triangular since it is the basic shape that usually considered by engineers The results show that the deduced parameters are optimal and provide a good results.