Chattering-free LS-SVM sliding mode control

Abstract

Least squares support vector machine (LS-SVM) classifiers are a class of kernel methods whose solution follows a set of linear equations. In this work we present a least squares support vector machine sliding mode control (LS-SVM-SMC) strategy for uncertain discrete system with input saturation. The output of LS-SVM is used for replacing sign function of the reaching law in traditional sliding mode control (SMC). An equivalent matrix is constructed for input saturation condition in the scheme. Combined LS-SVM-SMC with linear Matrix Inequalities (LMIs), a chattering free control algorithm is applied in the uncertain discrete systems with input saturation. The feasibility and effectiveness of the LS-SVM-SMC scheme are demonstrated via numerical examples. As a result, compared with conventional SMC, the LS-SVM-SMC is able to achieve the desire transient response with input saturation. And there is no chattering in steady state while unmatched parameter uncertainty exists. © 2008 Springer-Verlag Berlin Heidelberg.