Adaptive cascade tracking control of USV for recovery task

Abstract

ObjectivesAiming at the high-precision recovery guidance control requirements of current stern ramp recovery technology, a self-adaptive cascade tracking control method for unmanned surface vessels (USVs) is proposed specifically for stern ramp recovery. MethodsBased on the technical requirements of stern ramp recovery, a motion model of an underactuated USV is established, and the generalized Kalman filter (GKF) algorithm is used to predict the navigation state and recovery position of the mother ship. Introducing the idea of constant bearing guidance combined with the sliding mode variable structure control theory, a stable cascade control system is constructed to solve tracking control problems during the recovery process. ResultsIt is proven that the USV can stably track the target, by analyzing the stability of the system through the Lyapunov theory and cascade theorem. ConclusionsThe simulation results show that the proposed control method gives the USV stable tracking performance and strong robustness against uncertain disturbances.

Keywords

• stern ramp recovery
• underactuated unmanned surface vehicle
• generalized kalman filter
• constant bearing navigation
• adaptive sliding mode control