Dynamic Sliding Mode Controller Based on Particle Swarm Optimization for Mobile Robot's Path Following

Abstract

In this paper, a vision-guided mobile robot's path following is studied. A dynamic sliding mode controller (DSMC) is designed based on the nonlinear kinematic model of the robot without linearization of the system and the stability of the controller is proved through Lyapunov function. Particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of the controller. Simulation analysis and experimental results demonstrate that the controller proposed can steer the robot to track the guide line accurately, which also show that the controller eliminates chattering problem effectively since the high-frequency chattering is transferred into the derivative of the control signal. The precision of the system can reach below 2 cm for distance error and 2 degree for orientation error.