Optimal Speed Controller Design of Commercial BLDC Motor by Adaptive Tabu Search Algorithm

Brushless direct current motors are widely used in many industries because of their high efficiency and long-life. This paper presents the application adaptive Tabu Search algorithm for system identification PID speed controller design to provide best output performance compared with those designed using well-known tuning method, Ziegler–Nichols approach. The proposed technique shows that includes control signal consideration process. As a result, resulting parameters can be implemented without limitations real devices, while method cannot as good response expected. results validated by simulation experiment which responses from evidently better than conventional method. Moreover, other artificial intelligence techniques such genetic algorithm, particle swarm optimization etc. also applied optimal process following concept this characteristics considered devices.