本文提出一种自适应和神经动力学相结合的轮式移动机器人路径跟踪控制方法.首先,设计运动学控制器用来获得机器人期望速度;其次,考虑机器人动力学模型参数的不确定性,利用模型参考自适应方法来设计动力学控制规律,使得机器人实际速度渐近逼近期望值;再次,为克服速度和力矩的跳变,加入神经动力学模型对控制器进行优化,并且通过Lypunov理论来证明整个控制系统的稳定性;最后仿真结果表明该控制方法的有效性. In this paper, a path-tracking control method for wheeled mobile robot based on adaptive and neuro-dynamics is proposed. First, the kinematic controller is designed to obtain the expected velocity of the robot. Secondly, considering the uncertainty of the parameters of the robot’s dynamic model, The adaptive control method is used to design the control law of the dynamics so that the robot actual speed approaches the expected value asymptotically. Thirdly, to overcome the jump of the speed and torque, the neural dynamic model is added to optimize the controller. The Lypunov theory is used to prove that the whole control The stability of the system; Finally, the simulation results show the effectiveness of the control method.