Adaptive robust control of the mobile manipulator based on neural network

This article describes an adaptive robust control algorithm of the mobile manipulator based on robust neural network to solve disturbances, nonlinearity, nonholonomic constraints between the mobile platform and the mounted manipulator. According to the nonlinear mapping ability of neural network and fast learning ability, neural network and robust control strategies are integrated into the adaptive control algorithm for the mobile manipulator with nonlinear and nonholonomic constraints. Basis on the mobile manipulator dynamics model and its modeling analysis, the controller can drive the trajectory tracking error of the mobile manipulator to converge to zero. The simulation results show that the algorithm has higher precision of trajectory tracking control and can achieve good control effect.