Adaptive Optimal Predictive Control Framework With Improved Prescribed Performance for Path Tracking in Underactuated Two‐Wheeled Mobile Robot

ABSTRACT In this paper, an adaptive optimal predictive control method based on improved prescriptive performance is proposed for the path tracking control of an underactuated two‐wheeled mobile robot. The system is challenging to control due to its underactuated characteristics and nonlinear dynamics behavior. To improve the robustness of the system under uncertainty and reduce the jitter phenomenon, a new control strategy is designed by combining the improved prescribed performance control with adaptive optimal predictive control. The method ensures that the system output can satisfy the prescribed performance requirements within a specific time range and recover the stable operation faster under certain disturbances through the design of reasonable soft‐constraint performance indexes. In addition, a rigorous stability analysis of the control system is carried out to demonstrate the boundedness of the error function and the transient and steady‐state performances specified by the output tracking error. Simulation results show that the proposed control method can significantly improve the stability and control accuracy of the system under disturbances.