Nonlinear generalized predictive control based on online least squares support vector machines

被引：0
|
作者：
Zhenkai Guo
Xinping Guan
机构：
[1] Ludong University,School of Mathematics and Statistics Science
[2] Shanghai Jiao Tong University,Department of Automation
[3] Ministry of Education of China,Key Laboratory of System Control and Information Processing
来源：
Nonlinear Dynamics | 2015年 / 79卷
关键词：
Nonlinear system; Generalized predictive control (GPC); Online least squares support vector machines;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
For a class of nonlinear discrete systems with unknown parameters, an adaptive direct generalized predictive control method based on online least squares support vector machines (OLS–SVM) is proposed. In the method, the OLS–SVM is used to design the controller directly, and an improved projection algorithm based on the tracking error is introduced to adjust the weights of the OLS–SVM adaptively, so the inverse matrix is avoided in the process of online real-time control. It is proved that the proposed method can make the tracking error converge to a small neighborhood of the origin. Simulation results have shown the correctness and effectiveness of the proposed method.
引用
收藏
页码：1163 / 1168
页数：5
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