Adaptive fixed-time command-filtered funnel control for nonstrict-feedback nonlinear systems with input saturation

This paper explores adaptive fixed-time control for nonstrict-feedback nonlinear systems affected by input saturation and external disturbances, employing a command-filtered approach. To manage input saturation nonlinearity, a smooth non-affine function approximates the saturation effect. Radial basis function networks (RBFNN) estimate unknown nonlinear functions of the system, while adaptive techniques combined with backstepping design form a fixed-time control strategy. The “explosion of complexity” issue from derivatives of virtual controllers is reduced using command filters. To address filter errors and improve over conventional methods such as dynamic surface control, an error compensation mechanism is added. The proposed strategy ensures effective transient and steady-state tracking performance by applying a funnel constraint function. Using fixed-time stability theory, the tracking error convergence within fixed time and the boundedness of closed-loop signals are validated. Simulation results confirm the scheme’s effectiveness.