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Optimal Design of PID Controller Using Modified Ant Colony System Algorithm

A novel intelligent design method for PID controller with optimal self-tuning parameters is proposed based on the modified ant colony system (ACS) algorithm. By testing four different control systems with the typical characteristic such as high order, time delays, and nonlinearity, the proposed ACS-PID algorithm has been demonstrated to have an adaptive property and robust stability in searching for the optimal PID controller parameters. By comparing with the PID controllers designed by use of the differential evolution (DE), the real-coded genetic algorithm (GA), and the simulated annealing (SA), the proposed ACS-PID controller has been demonstrated to be better than or equivalent to these PID controllers in control performance.