履带式移动机械臂的自适应模糊滑模控制

Adaptive fuzzy sliding mode control for crawler-type mobile manipulators

针对非线性及不确定性复杂环境下非完整移动机械臂控制系统,提出了一种基于自适应模糊控制和非奇异终端滑模控制相结合的轨迹跟踪控制方法。该方法在对非完整移动机械臂建立动力学模型的基础上,采用模糊高斯基函数神经网络的非线性逼近性能,优化补偿常规方法在移动机械臂系统中难以解决的系统未知参数不确定性,并通过应用非奇异终端滑模控制来消除未知外界干扰和模糊控制逼近误差对系统的影响,提高了系统的鲁棒性和控制性能。应用Lyapunov稳定性理论,证明了控制系统的稳定性,仿真试验结果验证了该方法的有效性和优越性。

This paper proposes a trajectory tracking control method for nonlinear and uncertainty nonholonomic mobile manipulator control system based on adaptive fuzzy control and non-singular terminal sliding mode control. First, a dynamic model for the nonholonomic mobile manipulator is established. The Fuzzy Gaussian Potential Function Neural Networks （FGPFNN） is employed, because of its nonlinear approximation performance, to compensate the uncertainties of unknown parameters of the system optimally. Second, the non-singular terminal sliding mode control is proposed in order to eliminate the influences of unknown outside interference and approximation errors on the system. Finally, the stability theorem of the control system is obtained by applying the Lyapunov stability theory. Simulation results demonstrate the effectiveness and superiority the proposed control method.