期刊
AUTOMATICA
卷 77, 期 -, 页码 353-359出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2016.11.024
关键词
Underactuated surface vessel; Adaptive observer; Neural network; Input saturation
资金
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [NRF-2012R1A1A1041216]
- National Research Foundation of Korea [2012R1A1A1041216] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This paper proposes an adaptive output feedback control for trajectory tracking of underactuated surface vessels (USVs). For the realistic dynamical model of USVs, we consider the USV model, where the mass and damping matrices are not diagonal. Moreover, except the mass matrix, the system parameters and nonlinearities of the USV are all assumed to be unknown. Despite this uncertain circumstance, we develop an adaptive observer based on the neural networks to estimate the velocity data of USVs. Then, an output feedback control law is designed by simultaneously considering the input saturation and underactuated problems. (C) 2016 Elsevier Ltd. All rights reserved.
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