A Novel Adaptive NARMA-L2 Controller Based on Online Support Vector Regression for Nonlinear Systems

被引：0
|
作者：
Kemal Uçak
Gülay Öke Günel
机构：
[1] Istanbul Technical University,Department of Control and Automation Engineering, Faculty of Electrical
来源：
Neural Processing Letters | 2016年 / 44卷
关键词：
Adaptive control; NARMA-L2 controller; NARMA-L2 model; Online support vector regression; SVR-NARMA-L2 controller;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this study, a novel nonlinear autoregressive moving average (NARMA)-L2 controller based on online support vector regression (SVR) is proposed. The main idea is to obtain a SVR based NARMA-L2 model of a nonlinear single input single output system (SISO) by decomposing a single SVR which estimates the nonlinear autoregressive with exogenous inputs (NARX) model of the system. Consequently, using the obtained SVR-NARMA-L2 submodels, a NARMA-L2 controller is designed. The performance of the proposed SVR based NARMA-L2 controller has been evaluated by simulations carried out on a bioreactor system, and the results show that the SVR based NARMA-L2 model and controller attain good modelling and control performances. Robustness of the controller in the case of system parameter uncertainty and measurement noise have also been examined.
引用
收藏
页码：857 / 886
页数：29
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