Tuning cascade PI(D) controllers in PMDC motor drives: A performance comparison for different types of tuning methods

This work presents a comparison between different tuning methods for cascade PI(D) controller parameters of the permanent magnet direct current (PMDC) motor drives. First, the classical method (CM) for cascade PI(D) tuning is explained and applied. It has been shown that the classical tuning approach requires some assumptions. Next, a heuristic optimization technique, the Bacterial Foraging Algorithm (BFA), has been introduced and implemented for the problem. Lastly, for the comparison, the Genetic Algorithm (GA) is applied for the cascade PI(D) tuning problem. The results for these three methods are compared and discussed. It is shown that the controller designed by BFA showed better dynamic performance.