Improved adaptive neural control for a class of MIMO time delay systems

Based on the principle of sliding mode control and property of Nussbaum-type functions, an improved adaptive neural control scheme is proposed for a class of MIMO nonlinear time-varying delay systems with unknown function control gains. By choosing appropriate Lyapunov-Krasovskii functionals, unknown time-varying delay uncertainties are compensated for. In this paper, the restriction of control gains is relaxed, and the system considered here is more general. By utilizing Young´s inequality, the assumption of time-varying delay uncertainties is relaxed. Moreover, only one parameter is adjusted in each subsystem, and the complexity of implementation is reduced. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. Finally, simulation results are provided to illustrate the effectiveness of the proposed approach.