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Multivariable Nonlinear Proportional-Integral-Derivative Decoupling Control Based on Recurrent Neural Networks

ZHANG Yana,b; CHEN Zengqiangb; YANG Penga; YUAN Zhuzhib   

  1. a Department of Automation, Hebei University of Technology, Tianjin 300130, China
    b Department of Automation, Nankai University, Tianjin 300071, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2004-10-28 Published:2004-10-28
  • Contact: ZHANG Yan

基于递归神经网络的多变量非线性PID解耦控制

张燕a,b;陈增强b;杨鹏a;袁著祉b   

  1. a Department of Automation, Hebei University of Technology, Tianjin 300130, China
    b Department of Automation, Nankai University, Tianjin 300071, China
  • 通讯作者:

    张燕

Abstract: A nonlinear proportional-integral-derivative (PID) controller is constructed based on recurrent neural networks. In the control process of nonlinear multivariable systems, several nonlinear PID controllers have been adopted in parallel. Under the decoupling cost function, a decoupling control strategy is proposed. Then the stability condition of the controller is presented based on the Lyapunov theory. Simulation examples are given to show effectiveness of the proposed decoupling control.

Key words: process control, reaction engineering, neural network

摘要: A nonlinear proportional-integral-derivative (PID) controller is constructed based on recurrent neural networks. In the control process of nonlinear multivariable systems, several nonlinear PID controllers have been adopted in parallel. Under the decoupling cost function, a decoupling control strategy is proposed. Then the stability condition of the controller is presented based on the Lyapunov theory. Simulation examples are given to show effectiveness of the proposed decoupling control.

关键词: 非线性PID;递归神经网络;解耦控制;多变量