LS-SVM Based Stable Generalized Predictive Control

被引：1
|
作者：
Bin, Liu [1 ]
Zheng, Jiang [1 ]
Fang Kangling [1 ]
机构：
[1] Wuhan Univ Sci & Technol, Minist Educ, Engn Res Ctr Met Automat & Detecting Technol, Wuhan 430081, Hubei, Peoples R China
来源：
Proceedings of the 27th Chinese Control Conference, Vol 2 | 2008年
关键词：
Stable generalized predictive control; Least squares support vector machine; Pulp washing process;
D O I：
10.1109/CHICC.2008.4605257
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A stable generalized predictive controller (SGPC) based on least squares support vector machine(LS-SVM) model is presented. For a given closed-loop control configuration, a receding horizon optimal control law which can stably track the constant set point free-offset is obtained by optimizing the objective function over the future reference signal, The system model is built by using LS-SVM, and then the obtained model is transformed into input-output relation of the controlled system, which can be employed by SGPC directly. The detailed implementation of the presented algorithm is given and the algorithm is applied into a pulp washing process. The simulation results revealed the effectiveness and merit of the presented algorithms.
引用
收藏
页码：58 / 61
页数：4
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