Adaptive Backstepping Sliding Mode Tracking Control for Underactuated Unmanned Surface Vehicle With Disturbances and Input Saturation

This paper presents an adaptive backstepping sliding mode tracking control method for underactuated unmanned surface vehicle. The tracking controller is designed by combining backstepping and adaptive sliding mode control technology. The virtual control law is used to replace the control strategy of position error, and the position tracking control is transformed into velocity control, which can effectively avoid the input saturation and singular value problem existing in the design of traditional backstepping control law. The neural shunt model method is used to solve the differential explosion problem caused by virtual control law. The adaptive technology based on backstepping sliding mode theory is introduced to compensate the model uncertainty and time-varying disturbances of the system, and the robustness of the underactuated USV is enhanced by this method in the unknown environment. Based on the Lyapunov stability theory, it is proved that the control system error is ultimately uniformly bounded. The simulation results show that the proposed adaptive backstepping sliding mode tracking control method can achieve stable tracking in the case of system parameter uncertainty and time-varying disturbances, so it can be concluded that this method is reasonable and effective.

Automated summary

This paper proposes an adaptive backstepping sliding mode tracking control method for underactuated unmanned surface vehicles, which combines backstepping and adaptive sliding mode control technology. By using a virtual control law to replace the position error control strategy and introducing adaptive technology based on backstepping sliding mode theory, the control system's robustness is enhanced in unknown environments. Simulation results demonstrate the effectiveness of the proposed method in achieving stable tracking under system parameter uncertainty and time-varying disturbances.