Abstract
To solve the trajectory tracking problem of fully actuated ships with model uncertainties and unknown external disturbances, a RBF neural network dynamic surface sliding mode output feedback control based on extended state observer (ESO) is proposed. For most control systems of ships, only position and heading are measurable, the nonlinear third order ESO is constructed to estimate ship position, velocity and external disturbances. Then the dynamic surface sliding mode output feedback control is designed to achieve high-precision ship trajectory tracking control, and the RBF neural network is used to approximate and compensate the model uncertainties. Lyapunov stability theory is applied to prove the error signals in the trajectory tracking closed-loop control system are uniformly ultimately bounded. Finally, simulations are carried out to verify theoretical results.
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