Command-filter-based predefined-time adaptive tracking control for nonlinear systems with time-varying state constraints and input saturation

This paper investigates the adaptive tracking control problem for a class of uncertain nonlinear systems subject to time-varying state constraints and input saturation. To avoid the repeated differentiation encountered in conventional recursive design, a command-filter-based predefined-time adaptive control scheme is developed. Fuzzy logic systems (FLSs) are employed to approximate the unknown nonlinear functions, while a fuzzy observer is constructed to estimate the unmeasurable states. In addition, an auxiliary compensation mechanism is introduced to reduce the influence of filtering errors, and a smooth saturation decomposition together with an auxiliary signal is incorporated to handle the mismatch between the designed control input and the actual actuator output caused by input saturation. By combining recursive design with a time-varying barrier Lyapunov function (BLF), it is shown that all closed-loop signals remain bounded, the prescribed state constraints are not violated, and the tracking error enters a small neighborhood of the origin within a predefined time. Finally, simulation results based on an RLC circuit example are provided to demonstrate the effectiveness of the proposed method.