Genetic Algorithm Optimization and Implementation of Velocity Control PI Controller for Cart Follower Application

One of the main important aspect in designing a cart follower for wheelchair user is regulating the velocity of the cart itself so that it follows the wheelchair users. Two of the most important performance parameters are overshoot percentage and settling time. Small overshoot percentage is important so that there is no sudden rise in velocity that could reduce the lifespan of hardwares. Faster settling time is needed as the cart need to adapt with various speed of wheelchair as the cart need the shortest time to achieve steady state condition. Genetic Algorithm tuning method by using ITSE error criterion is used in optimizing the PI controller. In real application, GA yields the best performance in settling time and overshoot percentage, 31.96% and 13.63% better than AMIGO, the second best in these performance parameters. GA produce 140.135% better rise time than AMIGO. Eventhough SIMC and ZN is better in terms of rise time, oscillatory responses and huge overshoot percentage which is 31.73% and 180.75% respectively make both of the tuning methods are unfit in this application. Therefore, GA tuning methods is determined to be the best to be used in the application of velocity control PI controller for cart follower.