A fault-tolerant control method for distributed unmanned surface vessels formation with communication link faults

Unmanned surface vehicle (USV) formation control in marine environments is challenged by the underactuated nature of USV dynamics, two-dimensional operating constraints, and unpredictable environmental disturbances. Traditional fault-tolerant control (FTC) methods for unmanned systems are difficult to directly implement in USV formation systems, especially when subject to communication link failures. This paper introduces an innovative distributed FTC framework tailored for the coordination of USV formations, especially in challenging environments. Firstly, to overcome the limitation of insufficient control inputs due to underactuation, head nodes are constructed within the formation, enabling effective command dissemination and simplifying the influence of external disturbances such as friction. Secondly, a virtual leader is introduced to generate an ideal reference trajectory for the formation, which enhances overall robustness. Building upon this, a distributed FTC strategy is developed based on an adaptive state observer and the virtual leader-following control method. The observer adaptively estimates the system states and fault information in real time, while a backstepping-based formation controller compensates for both actuator and communication link faults in a distributed manner. Extensive simulation studies have been conducted to evaluate the fault tolerance mechanisms in distributed systems, which are crucial for maintaining system stability and data integrity in the face of potential node or network failures. Studies demonstrate significant improvements over existing methods in terms of fault resilience, trajectory accuracy, and formation robustness. It can be observed that the FTC approach effectively suppresses steady-state oscillations and maintains errors at the order of 10 ⁻⁴  m, whereas the non-FTC case exhibits significantly larger oscillations during the same time interval and even shows a tendency toward divergence at certain moments.