Reduced-Order Observer-Based Adaptive Fuzzy Self-Triggered Control for Fractional Order Nonlinear Systems Without Feasibility Conditions
Heng Liu, Hanlin Dong, Yongping Pan
Abstract
Traditional constraint control tends to impose indirect constraints on system states through intermediate tracking errors, so verifying the feasibility conditions is necessary, which usually results in a mismatch between actual constraint performance and constraint objectives. This article proposes an adaptive output feedback backstepping self-triggered (ST) control scheme for uncertain nonlinear fractional order systems with unilateral full state constraints and partially immeasurable states. A stable reduced-order observer is constructed to estimate immeasurable constraint system states, while ensuring that state constraints are met. Considering that event-triggered strategy requires real-time monitoring of control signals to update measurement errors, a ST scheme is proposed to avoid this drawback. Simultaneously, a new nonlinear mapping is constructed to complete the unilateral state constraint problem while satisfying the convexity condition of mapping functions. The designed controller not only avoids the Zeno behavior but also guarantees the convergence of tracking errors and the boundedness of closed-loop system signals. Finally, comparative simulation and actual case are provided to verify the validity and practical value of the proposed control strategy.