Adaptive Multi-dimensional Taylor Network Control for Stochastic Nonlinear Systems with Full State Constraints and Dead-zone Input

In this paper,the stochastic nonlinear systems with full state constraints and dead-zone input are considered in the same framework for the first time,and a new adaptive controller based on MTN is designed.Firstly,for the dead-zone input constraint problem,the characteristic function is introduced to avoid the nonlinearity of the dead-zone.Secondly,in the process of adaptive control design,MTN technology is employed to approximate the nonlinear structure generated in backstepping,and a simple controller is designed.By constructing the barrier Lyapunov functions(BLFs) to deal with the full state constraint problem,the proposed scheme ensures that all states of the closed-loop system do not exceed the constraint limit.Then,Lyapunov stability theory is used to analyze the stability.Finally,two simulation examples are given to illustrate the effectiveness and applicability of the proposed scheme.