Trajectory Tracking for Wheeled Mobile Robot Using Lyapunov-Based Model Predictive Control

This paper investigates the trajectory tracking control problem for wheeled mobile robots (WMRs) and proposes a novel Lyapunov-based model predictive control (LMPC) strategy. By incorporating the Lyapunov direct method into the model predictive control (MPC) framework, optimal control signals are obtained to achieve accurate trajectory tracking. The proposed method utilizes the Lyapunov direct method to design the control laws, and then incorporate the control laws into the optimization problem to construct the contractive constraint. Based on the contractive constraint, the stability of the controlled system is ensured. Besides, the recursive feasibility of the LMPC problem is analyzed and guaranteed by ensuring that the auxiliary control laws satisfy the input limitations. Finally, simulations and real-time experiments are conducted to verify the applicability and effectiveness of the proposed method.