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基于多信号源的神经模糊Hammerstein-Wiener模型研究

贾立 杨爱华 邱铭森

贾立, 杨爱华, 邱铭森. 基于多信号源的神经模糊Hammerstein-Wiener模型研究. 自动化学报, 2013, 39(5): 690-696. doi: 10.3724/SP.J.1004.2013.00690
引用本文: 贾立, 杨爱华, 邱铭森. 基于多信号源的神经模糊Hammerstein-Wiener模型研究. 自动化学报, 2013, 39(5): 690-696. doi: 10.3724/SP.J.1004.2013.00690
JIA Li, YANG Ai-Hua, CHIU Min-Sen. Research on Multi-signal Based Neuro-fuzzy Hammerstein-Wiener Model. ACTA AUTOMATICA SINICA, 2013, 39(5): 690-696. doi: 10.3724/SP.J.1004.2013.00690
Citation: JIA Li, YANG Ai-Hua, CHIU Min-Sen. Research on Multi-signal Based Neuro-fuzzy Hammerstein-Wiener Model. ACTA AUTOMATICA SINICA, 2013, 39(5): 690-696. doi: 10.3724/SP.J.1004.2013.00690

基于多信号源的神经模糊Hammerstein-Wiener模型研究

doi: 10.3724/SP.J.1004.2013.00690
详细信息
    通讯作者:

    贾立

Research on Multi-signal Based Neuro-fuzzy Hammerstein-Wiener Model

  • 摘要: 面对复杂工业过程控制的需求, 设计一种结合数据信息的特殊模型结构, 在保证控制系统有效性的前提下通过模型的结构来简化控制器的求解是亟待解决的问题. 为此, 本文提出一种基于多信号源的神经模糊Hammerstein-Wiener模型, 突破传统的迭代分离方法, 通过组合式多信号实现Hammerstein-Wiener模型中神经模糊非线性环节和线性环节的分离, 同时设计了神经模糊模型参数的非迭代优化算法, 将研究结果拓广到分段非线性系统,改善了模型的适用范围. 该算法保证了模型的预测精度,具有逼近较强非线性过程的能力. 在此基础上设计了基于神经模糊Hammerstein-Wiener模型的控制系统, 利用模型的特殊结构将非线性系统的控制问题简化为线性系统的控制问题, 采用简单的PID控制器便能达到较好的控制效果.仿真结果验证了上述方法的有效性.
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出版历程
  • 收稿日期:  2012-05-11
  • 修回日期:  2012-10-12
  • 刊出日期:  2013-05-20

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