Event-Triggered Fault-Tolerant Control for Uncrewed Marine Vehicle System With Actuator Fault and Disturbance

This paper proposes a fault tolerant control strategy for unmanned marine vehicles (UMVs) suffering from unknown actuator bias faults to avoid the structural complexity of conventional T-S fuzzy model. A fault observer is introduced to estimate actuator fault through online learning for real-time control input compensation. Further, to conserve network resources, an adaptive frequency event-triggered mechanism (AFETM) is applied. Unlike conventional event-triggered control methods that use fixed thresholds, AFETM dynamically adjusts the triggering condition based on historical transmission frequency and error, effectively reducing unnecessary data transmission. Moreover, instead of the traditional dual-network adaptive dynamic programming structure, a single critic network is employed to solve the Hamilton-Jacobi-Isaacs equation, significantly reducing computational burden and parameter complexity. Additionally, the stability of the UMV system is analyzed using the Lyapunov stability theorem, which demonstrates that the system states are uniformly ultimately bounded (UUB) under the proposed method. Simulation results demonstrate that the proposed AFETM reduces communication load by 99.6% and 25.4% compared with time-triggered mechanisms static and event-triggered methods, while ensuring UUB stability of the system states under actuator faults and disturbances.