Model free adaptive support vector regressor controller for nonlinear systems

被引：13

作者：

Ucak, Kemal ^{[1
]}

Gunel, Gulay Oke ^{[2
]}

机构：

[1] Mugla Sitki Kocman Univ, Fac Engn, Dept Elect & Elect Engn, TR-48000 Kotekli, Mugla, Turkey

[2] Istanbul Tech Univ, Fac Elect & Elect Engn, Dept Control & Automat Engn, TR-34469 Istanbul, Turkey

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2019年 / 81卷

关键词：

Adaptive control; Direct adaptive control; Model free adaptive control(MFAC); Model free SVR controller; Online support vector regression; SVR controller; GENERALIZED PREDICTIVE CONTROL; FEEDBACK; DESIGN;

D O I：

10.1016/j.engappai.2019.02.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this study, a novel model free support vector regressor controller (MF-SVRcontroller) is introduced for nonlinear dynamical systems. For the adaptation mechanism, a model free closed-loop margin which is a function of tracking error is derived and it is used to optimize the parameters of MF-SVRcontroller. The effectiveness of the adjustment mechanism and closed-loop performance of the MF-SVRcontroller have been examined by simulations performed on continuously stirred tank reactor (CSTR) and bioreactor benchmark systems. In order to observe the impacts of the removal of the model estimation block in control architecture, the performance of the MF-SVRcontroller is compared with a model based support vector regressor controller (MB-SVRcontroller) and SVM-based PID controller. The results indicate that MF-SVRcontroller diminishes the computational load of MB -SVRcontroller at the cost of a small amount of decrease in tracking performance.

引用

页码：47 / 67

页数：21

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