Efficient Steering Control for Long-Term Unmanned Surface Vehicle

Long-term unmanned surface vehicle (USV) is an effective means in ocean environmental monitoring and target detection for extended periods. Efficient steering control is the basis and premise for long-term USV to improve the adaptability and the endurance ability in complex sea states. In this paper, an efficient control algorithm is developed with the aid of fuzzy inference system and dynamic surface control technology. Specifically, based on data mining technology the fuzzy inference system is employed to identify the unknown yaw dynamics for the USV in presence of sea environmental disturbance and measurement noises. Besides, a robust adaptive steering law is established by using the dynamic surface control (DSC) design approach in Lyapunov stability analysis. In simulation, the simulation object is the independent designed “Lanxin” USV of Dalian Maritime University in China. Simulation results are given to validate the efficacy of the proposed method.