FUZZY PID CONTROLLER DESIGN USING GENETIC ALGORITHM

Abstract

Convectional PID controllers have been developed and applied for about half of a century for many industrial applications. However, it has been known that conventional PU) controllers generally do not work well for nonlinear systems, higher order and time delayed linear systems, and particularly complex and vague systems that have no precise mathematical models. To overcome these difficulties various types of modified conventional PID controllers such as auto tuning and adaptive Fuzzy PID controllers were developed lately. The present work deals with first design of PID, self tuning Fuzzy PD (FPD) and Fuzzy PID (FPID) controller applied for a dc servomotor model and later optimal Fuzzy PID controller design has been theoretically studied and analyzed. Genetic Algorithms are used to tune the scaling factors of fuzzy PID controller parameters like GE, GD and GH. In this work IAE, ITAE and ISE are compared with that of conventional controllers. Simulation results are used to show that the proposed Fuzzy PID controller produces superior control performance than the conventional PID controllers, particularly in case of complex and nonlinear systems.