Genetic Algorithms for Trajectory Tracking of Mobile Robot Based on PID Controller

This paper investigates trajectory tracking for an autonomous nonholonomic wheeled mobile robot with virtual robot as reference trajectory. The standard proportional integral derivative (PID) is used for regulating the velocity of the follower robot such that the tracking errors are minimized between the follower and the reference trajectory. However using the PID controller solely for trajectory tracking produces poor results in the presence of noise or external disturbances. Hence genetic algorithms (GA) is applied in this paper to improve the performance of the PID controller in terms of control precision and speed of convergence. Moreover, communication between the follower and the virtual robot may fail very often in practice due to many raisons such as noise or external disturbances. Therefore, GA is applied again to predict the reference trajectory in case of communication disturbance. The simulation results demonstrate the effectiveness of the proposed GA-PID controller compared with the PID controller.