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Multivariable Nonlinear Proportional-Integral-Derivative Decoupling Control Based on Recurrent Neural Networks 被引量:6

Multivariable Nonlinear Proportional-Integral-Derivative Decoupling Control Based on Recurrent Neural Networks
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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. A nonlinear proportional-integral-derivative (PID) controller is constructedbased 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 ispresented based on the Lyapunov theory. Simulation examples are given to show effectiveness of theproposed decoupling control.
出处 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2004年第5期677-681,共5页 中国化学工程学报(英文版)
基金 SupportedbytheNationalNaturalScienceFoundationofChina(No.60174021andNo.60374037).
关键词 非线性PID 递归神经网络 解耦控制 多变量 process control reaction engineering neural network
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