Adaptive fault‐tolerant control for air cushion vehicle with fixed‐time convergence

Abstract

This paper proposes a fixed‐time convergence adaptive sliding mode fault‐tolerant controller (ASFTC) to address the air cushion vehicle (ACV) trajectory tracking problem under unknown environmental disturbances and actuator faults. The introduced method enhances the robustness and reduces the chattering of the controller, by proposing an initial state‐independent fixed‐time convergence method combined with a global sliding mode surface which has the advantage of quickly reaching the “sliding mode”. The model knowledge neural network (MKNN) method is employed to eliminate uncertain parameter effects, and it adjusts disturbance and fault estimates in real time based on tracking errors without the need for upper‐bound disturbance information and additional observer compensation. Finally, simulations validate the effectiveness of the proposed adaptive fault‐tolerant control system.