Observer-Based Finite-Time Adaptive Fuzzy Control for Nonlinear Systems with Full-State Constraints

Abstract

This paper investigates practical finite-time adaptive fuzzy control for uncertain nonlinear systems subject to full-state constraints and unmeasured state variables. To deal with the inaccessibility of some state variables, an observer is constructed. A state-dependent nonlinear mapping is introduced to ensure that all system states remain within their prescribed bounds. In contrast to typical barrier Lyapunov function (BLF)-based schemes, the presented method manages full-state constraints without imposing any extra prerequisites on virtual control signals. Fuzzy logic systems (FLSs) act as estimators for the unknown nonlinearities emerging in the control law design, while the integration of dynamic surface control techniques helps circumvent the “complexity explosion” characteristic of conventional backstepping approaches. Subsequently, a practical finite-time adaptive fuzzy tracking controller is constructed, which guarantees the semi-global practical finite-time stability of the closed-loop system, with all closed-loop signals remaining bounded for all time and the tracking error converging to a residual set within finite time. Simulation results demonstrate that the tracking error enters a small residual set within finite time and that all system states remain within their prescribed constraints.