引用本文:解学军，王远.基于神经元网和带死区的最小二乘算法的非线性离散时间系统的自适应控制[J].控制理论与应用,1999,16(3):355~360.[点击复制]
Xie Xuejun and Wang Yuan.Adaptive Control of Nonlinear Discrete-Time Systems Using Neural Networks and Least Squares Algorithm with Dead-Zone[J].Control Theory and Technology,1999,16(3):355~360.[点击复制]
基于神经元网和带死区的最小二乘算法的非线性离散时间系统的自适应控制
Adaptive Control of Nonlinear Discrete-Time Systems Using Neural Networks and Least Squares Algorithm with Dead-Zone
摘要点击 974  全文点击 465  投稿时间：1998-03-02  修订日期：1998-09-09
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DOI编号  
  1999,16(3):355-360
中文关键词  非线性系统  多层神经元网  带死区的最小二乘算法  自适应控制
英文关键词  Nonlinear systems  multilayer neural networks  least squares algorithm with dead-zone  adaptive control
基金项目  
作者单位
解学军，王远  
中文摘要
      针对非线性离散时间系统，提出了一种用带死区的最小二乘算法去调节神经网参数的算法，同其他算法相比，这种算法具有非常高的收敛速度，对于这种自适应控制算法，证明了闭环系统的所有信号是有界的，跟踪误差收敛到以零为原点的球中。
英文摘要
      Multilayer neural networks are used in a nonlinear discrete0time adaptive control problem. The weights of the neural networks are uqdated by using least squares (LS) algorithm with dead-zone. LS algorithm has much superior rate of convergence compared with gradient algorithm and δ-modification algorithm. For the adaptive control algorithm, we prove that: 1) all signals in the closed-loop systems are bounded; and 2) the tracking error converges to a bounded ball.