Trajectory Tracking Control of Mobile Robot Based on RMPC

Mobile robots can replace humans in harsh environments to accomplish many important tasks at a lower cost. Trajectory tracking control is a research hotspot in the field of mobile robot research. In this paper, a trajectory tracking control method based on robust model predictive control (RMPC) is proposed for wheeled mobile robot. Firstly, considering the control input constraints, the RMPC trajectory tracking controller is designed. Secondly, in order to effectively deal with the influence of disturbance, an auxiliary feedback controller composed of the error between the optimal state and the actual system state is designed for the actual control system of the robot with disturbance, so that the actual system state is maintained in the 'Tube' invariant set centered on the nominal trajectory, and the actual system state reaches the nominal trajectory, and finally reaches the equilibrium point along the nominal trajectory. Finally, the simulation and experimental verification of the mobile robot are carried out. The simulation results show that the RMPC method improves the trajectory tracking accuracy of the mobile robot, has a good trajectory tracking effect in terms of convergence speed and tracking accuracy, and can complete the task more safely and reliably.