存在关节力矩输出死区及外部干扰的漂浮基空间机械臂积分滑模神经网络自适应控制  

Integral sliding mode neural network adaptive control for the free-floating space manipulator with joint torque output dead-zone and external disturbance

作　　者：黄小琴 陈力[1,2] HUANG Xiao -qin;CHEN Li(School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou 350116,China;Collaborative Innovation Center of High End Equipment Manufacturing in Fujian,Fuzhou 350116,China)

机构地区：[1]福州大学机械工程及自动化学院,福州350116 [2]福建省高端装备制造协同创新中心,福州350116

出　　处：《计算力学学报》2018年第6期713-718,共6页Chinese Journal of Computational Mechanics

基　　金：国家自然科学基金(11372073;11072061);福建省工业机器人基础部件技术重大研发平台(2014H21010011)资助项目

摘　　要：探讨了载体位置和姿态都不受控时,漂浮基空间机械臂在带有关节力矩输出死区及外部干扰情况下轨迹跟踪的控制算法设计问题。死区与外部干扰影响系统的跟踪精度与稳定性。为此引入积分型切换函数,减少外部干扰引起的稳态误差,并利用径向基函数神经网络逼近动力学方程的未知部分,设计了一种积分滑模神经网络控制方案。控制算法的优点是,在死区斜率与边界参数不确定及最优逼近误差上确界未知的条件下,可以利用最优逼近误差、死区及干扰的补偿项来消除影响。李亚普诺夫稳定性分析证明了闭环系统的稳定性,且轨迹跟踪误差将收敛到0的某个小邻域内。仿真算例证实了该控制算法的有效性,实现了空间机械臂的轨迹跟踪控制。The trajectory tracking control of a free-floating space manipulator with joint torque output dead-zone and external disturbance is studied.Dead-zone and external disturbance will affect the control precision and stability of the system.The steady state error caused by external disturbance is reduced by use of the integral variable structure function,and the radial basis function neural network is used to approximate unknown part of the dynamic equation.Then,an integral sliding mode neural network control is proposed.In the scheme,effects due to the unknown slope and boundary of the dead-zone are eliminated by introducing dead-zone and disturbance compensation,and the effects due to unknown supremum of the optimal approximation error are eliminated by the optimal approximation error.The Lyapunov stability analysis proves that the closed-loop control system is stable and the trajectory tracking error converges to a neighborhood of zero.Simulation results show the effectiveness of the control scheme and realize trajectory tracking control of the space manipulator.

关 键 词：漂浮基空间机械臂系统 关节力矩输出死区 外部干扰 积分滑模神经网络 轨迹跟踪 

分 类 号：TP241[自动化与计算机技术—检测技术与自动化装置] O231[自动化与计算机技术—控制科学与工程]