SVM based adaptive inverse controller for excitation control

Abstract

An adaptive inverse controller based on support vector machines (SVM) was designed for excitation control. Two SVM networks were utilized in the controller, one is SVM identifier (SVMI) and the other is SVM inverse controller (SVMC). The plant was identified by SVMI, which provided the sensitivity information of the plant to SVMC. SVMC was established using inverse system method as the pseudoinverse model. Both SVMI and SVMC are offline learned firstly and are online trained using back propagation algorithm. To guarantee convergence and for faster learning, adaptive learning rates and convergence theorems are developed. Simulations show that this controller has better performance in system damping and transient improvement. © Springer-Verlag Berlin Heidelberg 2007.