Adaptive Bacterial Foraging Optimization Based Tuning of Optimal PI Speed Controller for PMSM Drive

Abstract

Speed regulation with conventional PI regulator reduces the speed control precision because of disturbances in Motor and load characteristics, leading to poor performance of whole system. The values so obtained may not give satisfactory results for a wide range of speed. This paper implements, a new tuning algorithm based on the foraging behavior of E-coli Bacteria with an adaptive chemotaxis step, to optimize the coefficients of “Proportional-Integral” (PI) speed controller in a Vector-Controlled Permanent Magnet Synchronous Motor (PMSM) Drive. Through the computer simulations, it is observed that dynamic response of Adaptive bacterial foraging PI (ABF-PI) controller is quite satisfactory. It has good dynamic and static characteristics like low peak overshoot, low Steady state error and less settling time. The ABF technique is compared with “Gradient descent search” method and basic “Bacterial Foraging” Algorithm. The performances of these methods are studied thoroughly using “ITAE” criterion. Simulations are implemented using Industrial Standard MATLAB/SIMULINK.