具有H跟踪特性的不确定性机器人神经网络控制

丁国锋, 王孙安, 林廷圻, 史维祥

丁国锋, 王孙安, 林廷圻, 史维祥. 具有H跟踪特性的不确定性机器人神经网络控制[J]. 机器人, 1997, 19(5): 338-343.
引用本文: 丁国锋, 王孙安, 林廷圻, 史维祥. 具有H跟踪特性的不确定性机器人神经网络控制[J]. 机器人, 1997, 19(5): 338-343.
DING Guofeng, WAN Sun’an, LIN Tingqi, SHI Weixiang. NEURAL NETWORK CONTROL OF UNCERTAINTY ROBOTIC MANIPULATOR WITH H TRACKING PERFORMANCE[J]. ROBOT, 1997, 19(5): 338-343.
Citation: DING Guofeng, WAN Sun’an, LIN Tingqi, SHI Weixiang. NEURAL NETWORK CONTROL OF UNCERTAINTY ROBOTIC MANIPULATOR WITH H TRACKING PERFORMANCE[J]. ROBOT, 1997, 19(5): 338-343.

具有H跟踪特性的不确定性机器人神经网络控制

详细信息
    作者简介:

    丁国锋:男,27岁,博士.研究领域:智能控制、鲁棒控制、预测控制、故障诊断等.
    王孙安:男,41岁,副教授.研究领域:机电系统的模糊控制、鲁棒控制等.

NEURAL NETWORK CONTROL OF UNCERTAINTY ROBOTIC MANIPULATOR WITH H TRACKING PERFORMANCE

  • 摘要: 针对不确定性机器人提出一种具有H跟踪特性的神经网络(NN)控制器,使H∞控制理论与NN有机地结合起来.通过适当选择控制变量加权因子可以使由于NN近似误差以及外部干扰引起的误差动态衰减到期望的程度下.文中基于Lyapunov方法给出了NN学习自适应律,H跟踪特性的证明.最后通过在两自由度机器人控制中的应用表明该方案的可行性.
    Abstract: In this paper, a Neural Network control with H tracking performance for uncertainty robotic manipulator is proposed. The control scheme combined H control theory and NN adptive algorithm organically. If the weight to control variables is appropriatly chosen, the influence of both NN aproximation error and external disturbance can be attenuated to a desired level. Based on Lyapunov method, NN learning law is given and H tracking performance is illustrated. Finally, the developed controller is applied to a two-link robotic manipulator. Simulation results demonstrate that the control scheme is effective.
  • 1 Karakasoglu A,Sundareshan M K.A Recurrent Neural Network Based Adaptive Variable Structure Model-Following Control of Robotic Manipulator.Autamatic,1995,31(10):1495~1507
    2 Park J,Sandberg I W.Universal Approximation Using Radial Basis Function Networks.Neural Computation,1991,3:246~257
    3 Bor-Sen Chen,T S Lee,J H Feng.A Nonlinear H Cont rol Design in Systems Under Parameter Perturbation and Exeternal Disturbance.IN T J Cont rol,1994,59(2):439~461
    4 Limebeer,ect.A Game Theoretic Approach to H Control for Time-varying Systems.S IA M J Control and Optimization,1992,30:262~283
    5 Doyle J C K G,Khargonekar P P.State-space Solution to Standard H and H Control Problems.IEEE Trans,on Automatic Control,1989,34(8):831~847
    6 Anderson B D O,Moore J B.Optimal Control:Linear Quadratic Methods.Englewood Cliffs,N J:Prenticce Hall,1990
    7 Narendra K S,Annaswamy A M.Stable Adaptive Systems.Ennglewood Cliffs,N J:Prentice-Hall,1989
    8 刘延年,忻欣,冯纯伯.基于神经网络的一类非线性连续系统的稳定自适应控制.控制理论与应用,1996,13(1):70~75
计量
  • 文章访问数:  41
  • HTML全文浏览量:  632
  • PDF下载量:  148
  • 被引次数: 0
出版历程
  • 收稿日期:  1996-04-23

目录

    /

    返回文章
    返回
    x 关闭 永久关闭