Adaptive neural control of nonlinear time-delay systems with full state constraints and unmodeled dynamics

Abstract

An adaptive neural control method is developed for a class of full state constrained nonlinear systems with unmodeled dynamics and time-varying delays in this paper. An integral barrier Lyapunov function (iBLF) is used to every step in the backstepping procedure to ensure that the full state constraints are not violated. The unmodeled dynamics is dealt with by introducing a dynamic signal and the time-varying delays is disposed through constructing appropriate Lyapunov-Krasovskii functions. Moreover, it is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the full state constraints are not violated. A simulation example further demonstrates the effectiveness of the proposed control scheme.