机械手的神经网络稳定自适应控制器设计(英文)

Stable Adaptive Controller Design for Manipulators Using Neural Networks

本文针对机械手轨迹跟随控制问题，提出了一种稳定的神经网络自适应控制器设计方法，这里机械手的非线性动力学假设是未知的．提出方法是神经网络方法和扇区自适应变结构控制方法的集成．扇区变结构控制的作用有两个，其一是在系统神经网络控制失灵的情形下提供闭环系统的全局稳定性；其二是在神经网络的近似域内改进系统的跟随性能．本文采用李雅普诺夫稳定理论给出了系统的稳定性和跟随误差收敛性的证明，并且通过数字仿真验证了提出方法的有效性．

A stable neural network-based adaptive controller design for integrating a neuralnetwork (NN) approach with an adaptive implementation of the variable structure control with thesector is presented in this paper for the trajectory tracking control of a robot manipulator with unknown nonlinear dynamics. The variable structure control with the sector serves two purposes,one is to provide the global stability of the closed loop system when the system goes out of the NNcontrol, the other is to improve the tracking performance within the NN approximation region.The system stability and tracking error convergence are proved using Lyapunov stability theory,and the effectiveness of the proposed control approach is illustrated through simulation studies.