Indirect adaptive H ∞ output feedback control based on LS-SVM for uncertain nonlinear systems

Abstract

A novel framework of indirect adaptive H_∞ control method based on least squares support vector machines (LS-SVM) is proposed for a class of uncertain nonlinear systems with unavailable states and external disturbance. In this method, a state observer is designed to estimate the system states, and the LS-SVM is employed to approximate unknown nonlinear dynamics of the systems. The proposed adaptive H_∞ control is used to attenuate the effect on the tracking error caused by LS-SVM approximation errors and external disturbance. The parameters of the controller are self-tuned according to the adaptive law derived by using Lyapunov stability theory. The asymptotic stability of the proposed close-loop control system is proved. For evaluating the proposed method, numerical simulations of a chaotic system and an inverted pendulum system are presented. The simulation results verified its effectiveness and feasibility.