Disturbance estimation and control for trajectory tracking of wheeled mobile robots based on performance optimization

Abstract

The disturbance rejection control of the wheeled mobile robot (WMR) is important for stable trajectory tracking. However, the uncertain parameter and external disturbance can lead to the deterioration of tracking performance for the WMR. The focus of our study is on the topic of improving trajectory tracking control performance for WMR in the presence of external disturbances. Therefore, we discuss the disturbance observer-based double closed-loop control system scheme for managing a wheeled mobile robot WMR and achieving better trajectory tracking performance. First, the kinematic model of WMR is established to produce the virtual velocity in the outer based on the adaptive parameter estimation. In the inner loop, the dynamic model of WMR is established and the external disturbance is estimated by an extended state observer (ESO). Based on the estimation of ESO, the inner loop controller is designed and the trajectory tracking is achieved. Finally, to improve the tracking performance, an five dimensionality adaptive particle swarm optimization (PSO) algorithm is designed for the optimization of design parameters. The system stability is analyzed by the Lyapunov theory and the superiority of the proposed control scheme is verified by comparing with different control methods.