Adaptive Fuzzy State-Constrained Control Without Feasibility Conditions for Nonstrict Feedback Stochastic Nonlinear Systems With Input Delay

This paper studies the problem of adaptive fuzzy tracking for a class of nonstrict feedback stochastic systems with input delay and asymmetric state constraints. Input delay is addressed based on the Pade approximation and introducing an intermediate variable, then the control problem for the original systems is transformed into one for non-delay system. For state constraints in the system, this paper proposes nonlinear state dependent function (NSDF) instead of barrier Lyapunov function (BLF), which removes the feasibility conditions. By fuzzy logic system (FLS) and variable separation technology, this paper effectively solves algebraic rings created by nonstrict feedback structures. A fuzzy adaptive controller is proposed to ensure that all variables in the system are bounded in probability and the asymmetric state constraints are well kept all the time. Finally, simulation examples confirm the effectiveness of control strategy.