Adaptive NN State-Feedback Control for Stochastic High-Order Nonlinear Systems with Time-Varying Control Direction and Delays

Abstract EN

Nussbaum-type gain function and neural network (NN) approximation approaches are extended to investigate the adaptive state-feedback stabilization problem for a class of stochastic high-order nonlinear time-delay systems.

The distinct features of this paper are listed as follows.

Firstly, the power order condition is completely removed; the restrictions on system nonlinearities and time-varying control direction are greatly weakened.

Then, based on Lyapunov-Krasovskii functionand dynamic surface control technique, an adaptive NN controller is constructed to render the closed-loop system semiglobally uniformly ultimately bounded (SGUUB).

Finally, a simulation example is shown to demonstrate the effectiveness of the proposed control scheme.