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		Lianfei ZHAI,Tianyou CHAI.[en_title][J].Control Theory and Technology,2006,4(1):62~69.[Copy]

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LianfeiZHAI,TianyouCHAI
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Received:September 30, 2005Revised:January 04, 2006

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Nonlinear Decoupling PID Control Using Neural Networks and Multiple Models

Lianfei ZHAI , Tianyou CHAI

(Key Laboratory of Process Industry Automation, Ministry of Education, China; Research Center of Automation, Northeastern University, Liaoning Shenyang 110004, China)

Abstract:

For a class of complex industrial processes with strong nonlinearity, serious coupling and uncertainty, a nonlinear decoupling proportional-integral-differential (PID) controller is proposed, which consists of a traditional PID controller, a decoupling compensator and a feedforward compensator for the unmodeled dynamics. The parameters of such controller is selected based on the generalized minimum variance control law. The unmodeled dynamics is estimated and compensated by neural networks, a switching mechanism is introduced to improve tracking performance, then a nonlinear decoupling PID control algorithm is proposed. All signals in such switching system are globally bounded and the tracking error is convergent. Simulations show effectiveness of the algorithm.

Key words: Nonlinear Decoupling control PID Neural networks Multiple models Generalized minimum variance