Fault-tolerant target tracking control for the USV-UAV platform via the visual-based guidance and fault-tolerant control

This paper investigates a new cooperative trajectory tracking framework for the USV-UAV platform that uses a visual-based inversion guidance principle and sensor fault-tolerant control mechanism in the presence of external disturbances. This provides a new strategy for the platform independent of traditional navigation sensor. In the visual guidance module, the reference path of the USV-UAV would be calculated by utilization of the mapping technique according to the sampled images of the target vehicle obtained by an UAV. Further, the desired guidance signals are provided on basis of the fixed position relative to the target vessel. Associate with the developed guidance signal, a robust adaptive fault-tolerant control algorithm is designed to execute a tracking and monitoring mission of the unsupervised vehicles, where the constant and time-varying attitude sensor faults can be addressed by an application of the adaptive observer technique. Besides, the robust neural damping and dynamic surface control techniques are also introduced for tackling the problems of the model uncertainties, external disturbances and computational burden. Through the Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability property is proved. The advantages and the effectiveness of the proposed algorithm are evaluated using the numerical simulations.