Fault estimation for unmanned surface vehicles based on adaptive observer

This paper presents the design of an innovative adaptive observer method tailored specifically for unmanned surface vessels (USVs). The proposed method addresses several challenges inherent in the operation of USVs, including unknown sensor faults, unknown stuck actuator faults, and external disturbances. These issues, if left unaddressed, could significantly impact the performance and safety of USVs. The cornerstone of the proposed method is an online iterative adaptive mechanism, which is employed to reconstruct the states and faults of the USV. This mechanism leverages real-time data and iterative processes to adaptively update the state estimates and fault predictions, thereby enabling more accurate and timely fault detection and mitigation. In the final part of the article, we provide a comprehensive verification of the proposed design method. This is achieved through a detailed simulation analysis of the USVs model. The simulation results not only demonstrate the feasibility of the proposed method but also attest to its effectiveness in enhancing the reliability and safety of USVs.