PID-Controller Tuning of Brushless DC Motor by Using ACO (Ant Colony Optimization) Technique

ACO stands for Ant Colony Optimization which it automatically finds the best solution or the best PID controller parameters for the targeted control system. ACO algorithm is used as the technique for the PID controller parameters optimization. It functions in finding and obtaining optimum values of gain, integral time and derivative time for the PID controller. At the testing stage, the ACO algorithm is developed by using MATLAB. The ACO algorithm will calculate the ISE (Integral Square Error) for each set of PID parameters. and then comparison is done on the different values of ISE from different sets of PID parameters to choose the best PID parameters set with the lowest ISE. As a result, a performance curve of ACO that is as closed as to the set-point with high performances (lower overshoot value, shorter system dead time and settling time and lower ISE if compared to the conventional PID tuning methods) is obtained.