Robust finite-time sliding mode control of unmanned surface vehicle with active compensation of pose estimation uncertainty

Abstract

Robust control of Unmanned Surface Vehicles (USVs) is crucial for their safe and reliable navigation. The control methods of USV generally regard the results of pose estimation (such as GNSS/INS) as an accurate reference, but GNSS/INS is usually fluctuating and uncertain in the open water, which easily leads to large tracking errors or even control failure of USV. To this end, a robust sliding mode control of USV considering the active compensation of pose estimation uncertainty is innovatively presented, which can ensure the stability and accuracy of USV's control. The distinctive features of the proposed method are twofold: (i) To improve the pose estimation accuracy and obtain accurate uncertainty evaluation, an improved adaptive Kalman filtering considering the time-varying solution state is presented, which utilizes the convergence characteristics of INS and the time-varying features of GNSS solution state; (ii) By integrating pose estimation uncertainty assessment and active compensation, a Robust Finite-Time Sliding Mode Control (RFT-SMC) for a twin-propeller unmanned surface vehicle is developed to enhance tracking accuracy and anti-disturbance capability, and its convergence is established using a Lyapunov function, ensuring reliable operation of the USV even in the presence of uncertain pose estimation. Finally, verification experiments are offered to verify the effectiveness of the presented RFT-SMC method.