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基于神经网络的非线性系统复合内模控制
引用本文:陈娟,董翠英.基于神经网络的非线性系统复合内模控制[J].哈尔滨理工大学学报,2004,9(1):17-20.
作者姓名:陈娟  董翠英
作者单位:北京化工大学,信息学院,北京,100029;北京化工大学,信息学院,北京,100029
摘    要:利用RBF神经网络逼近连续非线性系统的α阶积分逆系统,并对原非线性系统及其逆系统构成的伪线性系统采用内模控制方法进行复合控制,从理论上分析了滤波器对跟踪误差的影响,仿真结果表明,内模控制与逆系统方法相结合的复合控制方案是处理非线性问题比较有效的方法之一。

关 键 词:RBF神经网络  逆系统  内模控制  伪线性系统  复合控制
文章编号:1007-2683(2004)01-0017-04
修稿时间:2003年10月14

Nonlinear Internal Model Control Strategy Based on Neural Network
CHEN Juan,DONG Cui-ying.Nonlinear Internal Model Control Strategy Based on Neural Network[J].Journal of Harbin University of Science and Technology,2004,9(1):17-20.
Authors:CHEN Juan  DONG Cui-ying
Abstract:RBF neural network is used to approximate to the a -integral inverse system of nonlinear continuous systems in this paper. And then pseudo - linear systems, which are composed of nonlinear continuous systems and its a -integral inverse system, are combined by the internal model control method, and the effects of filter for tracking error are analyzed. Simulation results show that internal model control (IMC) method is one of available methods for nonlinear systems.
Keywords:RBF neural network  inverse - system  internal model control  pseudo - linear system  combined control
本文献已被 CNKI 维普 万方数据 等数据库收录!
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