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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.12 P.1984-1988

http://doi.org/10.1631/jzus.2006.A1984


Predictive control of a class of bilinear systems based on global off-line models


Author(s):  ZHANG Ri-dong, WANG Shu-qing

Affiliation(s):  Institute of Advanced Process Control, National Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   zrd-el@163.com

Key Words:  Bilinear systems, Model predictive control (MPC), Adaptive control, Support vector machine (SVM)



Abstract: 
A new multi-step adaptive predictive control algorithm for a class of bilinear systems is presented. The structure of the bilinear system is converted into a simple linear model by using nonlinear support vector machine (SVM) dynamic approximation with analytical control law derived. The method does not need on-line parameters estimation because the system’s internal model has been transformed into an off-line global model. Compared with other traditional methods, this control law reduces on-line parameter estimating burden. In addition, its overall linear behavior treating method allows an analytical control law available and avoids on-line nonlinear optimization. Simulation results are presented in the article to illustrate the efficiency of the method.

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