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• W2334086641 abstract "<?Pub Dtl=?> In this paper, the authors study the problem of robust adaptive path-following control for underactuated ships with model uncertainties and nonzero-mean time-varying disturbance. A concise adaptive neural network (NN)-based control scheme is proposed using backstepping, feedforward approximations, dynamic surface control, and minimal learning parameter techniques. In addition, to tackle the strong couplings among state variables (including the underactuated state variable) and underactuated characteristics, much effort is put into guaranteeing semiglobal uniform ultimate boundedness of the ship motion control system. The outstanding advantage of this scheme is that the control law has a concise form and is easy to implement in practice due to a smaller computational burden, with only two online parameters being tuned to tackle the uncertainties. The simulation results demonstrate the effectiveness of the proposed algorithm, especially including the experiment in the simulated marine environment." @default.
• W2334086641 created "2016-06-24" @default.
• W2334086641 creator A5076298432 @default.
• W2334086641 creator A5081207814 @default.
• W2334086641 date "2014-10-01" @default.
• W2334086641 modified "2023-10-18" @default.
• W2334086641 title "Concise Robust Adaptive Path-Following Control of Underactuated Ships Using DSC and MLP" @default.
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• W2334086641 doi "https://doi.org/10.1109/joe.2013.2280822" @default.
• W2334086641 hasPublicationYear "2014" @default.
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