Adaptive Control of a Class of Non-Autonomous Systems Based on Least Square Support Vector Machine

A design method of adaptive controller is proposed based on least square support vector machine(LS-SVM) for a class of uncertain non-autonomous systems,in which LS-SVM is adopted to estimate the partially unknown nonlinear items in the object,and an on-line learning rule for the weight vectors of LS-SVM and the bias is derived.Lyapunov theory is used to strictly prove the uniform ultimate boundedness of the tracking errors of the whole closed-loop system,the controller parameters,the weight parameters and the bias of LS-SVM.The proposed control scheme can track any smooth target trajectory steadily and online,and the simulation result shows its effectiveness and feasibility.