期刊
JOURNAL OF MARINE SCIENCE AND ENGINEERING
卷 10, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/jmse10020279
关键词
barrier Lyapunov function; basis function network; minimum learning parameter; dynamic surface control; automatic berthing
This paper investigates the automatic berthing problem of underactuated surface vessels in the case of uncertain dynamics and yaw rate limitation. It proposes the use of differential homeomorphism coordinate transformation, radial basis function network, and barrier Lyapunov function to solve the underactuation problem. It also applies dynamic surface control technology and minimum learning parameters to tackle differential explosion problems and computational complexity. Simulation results show that the proposed method effectively limits the yaw rate and solves the influence of model uncertainty.
This paper investigates the automatic berthing problem of underactuated surface vessels in the case of uncertain dynamics and yaw rate limitation, given the importance of yaw rate control and the unmeasurable hydrodynamic parameters of the vessel at low speeds. First, we use the differential homeomorphism coordinate transformation to solve the problem of underactuation. Second, a radial basis function network (RBF) is introduced to approximate unknown nonlinear functions. Third, we apply the barrier Lyapunov function (BLF) approach to limit the yaw rate within a safe range. Fourth, we use dynamic surface control (DSC) technology and minimum learning parameters (MLP) to tackle the differential explosion problems in backstepping and computational complexity. Finally, Lyapunov stability theory proves that signals produced by the designed control scheme are bounded and effective. The simulation results show that, compared with the control scheme without BLF, the proposed method can effectively limit the yaw rate within a specific range and effectively solves the influence of the model uncertainly.
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