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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2002, Vol. 3 Issue (1): 57-59    DOI: 10.1631/jzus.2002.0057
Computer & Industrial Engineering     
Fuzzy NN based predictive control and its application to green liquor system
LI Jiang, ZHOU Wei, ZHANG Liang-jun, LI Ping
Institute of Industrial Process Control, Zhejiang University, Hangzhou 310027, China; College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  The fuzzy NN predictive control algorithm introduced in this paper uses fuzzy neural network to model the nonlinear MIMO process. Its training method that integrates LS and BP algorithm brings quick convergence. GPC algorithm is used as the predictive component. The fuzzy neural network has six layers, including input layer, output layer and four hidden layers. An application to a MIMO nonlinear process(green liquor system of the recovery system in a pulp factory shows that this algorithm has better performance than normal PID algrithm.

Key words： model predictive control      fuzzy neural networks      generalized predictive control     
Received: 07 November 2000     
CLC:  TP273.4  
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Cite this article:

LI Jiang, ZHOU Wei, ZHANG Liang-jun, LI Ping. Fuzzy NN based predictive control and its application to green liquor system. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2002, 3(1): 57-59.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2002.0057     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2002/V3/I1/57

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