Adaptive Control of Nonlinear Switched Output Feedback Systems with Unmodeled Dynamics and Constraints

Abstract

In this paper, robust adaptive control problem is discussed for a class of output feedback nonlinear switched systems with unmodeled dynamics and time-varying constraints. Based on the common Lyapunov function (CLF), an adaptive output feedback dynamic surface control (DSC) scheme is developed. Radial basis function neural networks are utilized to approximate unknown continuous functions, and K-filters and a dynamic signal are designed to estimate the unmeasured states and deal with the dynamic uncertainty. An asymmetric barrier Lyapunov function (ABLF) is introduced to handle output constraint. It is proved that the designed controller can guarantee the semi- global uniform ultimate boundedness (SGUUB) for all the signals in the closed-loop system under arbitrary switchings. The simulation results are provided to demonstrate the effectiveness of the proposed method.