针对含有驱动器及编队动力学的多非完整移动机器人编队控制问题,基于领航者-跟随者l-ψ控制结构,通过反步法设计了一种将运动学控制器与驱动器输入电压控制器相结合的新型控制策略。采用径向基神经网络(RBFNN)对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿。该方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,同时也确保了机器人编队在期望队形下对指定轨迹的跟踪;基于Lyapunov方法的设计过程,保证了控制系统的稳定与收敛;仿真结果表明了该方法的有效性。 Aiming at the problem of formation control of multi-nonholonomic mobile robots with actuator and formation dynamics, based on the pilot-follower l-ψcontrol structure, a kinematic controller and a driver input voltage controller are designed by backstepping method The new control strategy. Radial basis neural network (RBFNN) is used to estimate the nonlinear uncertainties of follower and navigator dynamically, and the neural network modeling error is compensated by adaptive robust controller. The proposed method not only solves the problem of parameter and nonparameter uncertainties in formation control of mobile robot, but also ensures the tracking of specified trajectory of robot formation under the expected formation. The design process based on Lyapunov method ensures the stability of the control system and The simulation results show the effectiveness of the method.