Adaptive fuzzy tracking control for constrained stochastic nonlinear systems with unknown control direction

Abstract

This paper studies the adaptive tracking control problem of stochastic nonlinear systems with asymmetric time-varying state constraints, input saturation and unknown control direction. Nussbaum function is adopted to handle the unknown control direction (UCD). A hyperbolic tangent function is employed to construct an auxiliary subsystem for addressing the input saturation issue, thereby transforming the original system into a new system with explicit inputs. Additionally, a fuzzy logic system is utilized to tackle the unknown nonlinear function. Combining the barrier Lyapunov function (BLF), a novel adaptive fuzzy controller is designed to ensure that all signals in the closed-loop system remain bounded, the state variables are constrained within asymmetric time-varying bounds, and the tracking error converges near the origin. Finally, the effectiveness of the proposed control scheme is verified through a simulation example.