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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2005, Vol. 6 Issue ( 5): 14-    DOI: 10.1631/jzus.2005.A0440
    
New predictive control algorithms based on least squares Support Vector Machines
LIU Bin, SU Hong-ye, CHU Jian
National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China; School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
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Abstract  Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on least squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built

Key words： Industrial Control Advanced Process Control Information Least squares Support Vector Machines      Linear kernel function      RBF kernel function      Generalized predictive control     
Received: 15 February 2004     
CLC:  TP273  
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LIU Bin
SU Hong-ye
CHU Jian
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LIU Bin, SU Hong-ye, CHU Jian. New predictive control algorithms based on least squares Support Vector Machines. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2005, 6( 5): 14-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2005.A0440     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2005/V6/I 5/14

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