Backstepping Controller for Trajectory Tracking of Wheeled Mobile Robot Based on Particle Swarm optimization

Abstract

This paper presents an improved controller based on particle swarm optimization (PSO) for trajectory tracking of wheeled mobile robots (WMR). On the basis of kinematic model, the authors adopt the Gauss error function in the virtual feedback variable design based on Backstepping. The stability of Backstepping controller is proved by Lyapunov function and Barbalet’s lemma. The unknown parameters of controller are tuned by PSO to gain better performance. Simulation with two different reference trajectory is carried out. The effectiveness of proposed controller is verified by simulation. Compared to original controller, simulation results show that the PSO-tuned controller can reduce the set time and smooth the tracking trajectory.