Observer-Based Fuzzy Adaptive Predefined Time Control for Uncertain Nonlinear Systems with Full-State Error Constraints

This paper studies the predefined time control design issue for uncertain nonlinear systems with full-state error constraints and unmeasurable states for the first time. Compared with existing works, this study enables the controlled system to stabilize within a predetermined time and ensures that the full-state tracking errors converge to a desired control accuracy range, even in the absence of measurable state information. Fuzzy logic systems (FLSs) are applied to handle unknown nonlinear dynamics, and FLSs-based nonlinear state observer is constructed to estimate unmeasurable states. With the universal barrier Lyapunov function and the dynamic surface control (DSC) technique, an output-feedback-based full-state error constrained control strategy with predefined time stability is proposed, in which a non-singular predefined time filter is constructed to avoid high computational complexity. Under this control strategy, the predefined time stability of the closed-loop system is achieved and the full-state error constraints are satisfied. Finally, a series of simulation results confirm the effectiveness and superiority of the proposed control strategy.