Cascade Integral Predictors and Feedback Control for Nonlinear Systems with Unknown Time-varying Input-delays

摘要

In this paper, we consider the problem of predictor design for nonlinear systems in the presence of unknown time-varying input-delays. A cascade integral high-gain predictor is proposed to estimate the future state. With a distinctive structure, the predictor can handle unknown delays and eliminate the "peaking phenomenon" during the transient period. Then, a predictor-based output feedback control is designed to guarantee the boundedness of system states. Lyapunov-Krasovskii functional and perturbation theories are used to prove the convergence of the estimation error and the closed-loop system. Finally, simulation results illustrate the superior performance of the cascade integral predictor compared to the standard high-gain predictor.