Adaptive Practical Fixed‐Time Tracking Control for Nonlinear Systems With Deferred Full‐State Constraints and Dead‐Zone Input

This paper studies the adaptive practical fixed‐time tracking control problem for nonlinear systems subject to deferred asymmetric time‐varying full‐state constraints and dead‐zone input. First, a dead‐zone input model, characterized by the combination of a linear input and a bounded disturbance, is designed to mitigate the negative impacts of dead‐zone input in nonlinear systems. Second, an error shifting function and an asymmetric time‐varying barrier Lyapunov function are established to address deferred constraints under unknown bounded initial conditions. Third, an adaptive practical fixed‐time tracking controller is established by integrating the asymmetric barrier Lyapunov function and neural networks. It is rigorously proved that all signals of closed‐loop systems maintain bounded, and the tracking error converges to a neighborhood of the origin within a fixed time, even if the initial value violates the constraint boundary. Finally, the effectiveness and superiority of the proposed control method are validated through a practical electromechanical system example and comparative simulations.