Trajectory Tracking Control for Mecanum-wheel Cambered Mobile Robots Based on Online Adaptive Critic Optimal Controller

Abstract

Mecanum-wheel cambered mobile robot (MWCMR) working in the Gas Insulated Switchgear (GIS) cavity is truly a complex system with highly non-linear. In order to control MWCMR for better trajectory tracking, a discrete intelligent trajectory tracking algorithm is presented in this paper. When realizing this algorithm, the kinematic model and dynamic model of MWCMR are also proposed, where the dynamic model is described by the second order Lagrange’s equation. This discrete intelligent trajectory tracking algorithm is a single network online adaptive critic optimal trajectory tracking control method, which is based on the idea of the critic-actuator structure and optimal control theory. The structure of the critic used for approximating the cost function adopts Neural Network (NN). Moreover, in order to ensure the stability of the system, a supervisor is also designed to make the difference of Lyapunov function negative definite. Then simulation is performed to test the trajectory tracking control algorithm for this GIS cavity robot, and the results are compared with the traditional neural network trajectory tracking control method and PD method. Finally, the effectiveness and advancement of this method are analyzed.