Title :
Adaptive control of a class of nonlinear systems using Support Vector Regression
Author :
George, Koshy ; Harshangi, Prashanth
Author_Institution :
E.E.S. Centre for Intell. Syst., Bangalore, India
Abstract :
In this paper we demonstrate an improvement in the transient tracking performance when a Support Vector Regression (SVR) is used to identify a nonlinear ARMA plant. We use an on-line version of SVR, and at each instant, the identified model is used to determine the appropriate control law. A further improvement in the transient performance is shown with the methodology of multiple models, switching, and tuning.
Keywords :
adaptive control; control system synthesis; nonlinear control systems; regression analysis; support vector machines; adaptive control; nonlinear ARMA plant; nonlinear systems; support vector regression; transient tracking performance; Adaptation model; Adaptive control; Artificial neural networks; Nonlinear systems; Support vector machines; Training; Transient analysis; Adaptive systems; NARMA; multiple models; support vector regression; switching and tuning;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-7814-9
DOI :
10.1109/ICARCV.2010.5707793
