期刊
OCEAN ENGINEERING
卷 174, 期 -, 页码 117-124出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2019.01.043
关键词
Underactuated ships; Undirected graph; Finite-time control; Formation control; Disturbance observer
资金
- National Natural Science Foundation of China [51679024, 51779029]
- Natural Science Foundation of Liaoning Province [20180520039]
- Fundamental Research Funds for the Central University [3132018301, 3132018304]
- National High Technology Research and Development Program of China [2015AA016404]
- University 111 Project of China [B08046]
- Program for Innovative Research Team in University [IRT17R13]
- Doctoral Scientific Research Foundation of Liaoning Province [20170520189]
- National Postdoctoral Program for Innovative Talents [BX201600103]
- China Postdoctoral Science Foundation [2016M601600]
This note investigates the decentralized finite-time formation control of underactuated unmanned surface vessels (USVs) in the presence of model uncertainty and environmental disturbance. In the algorithm, a novel adaptive finite-time disturbance observer (AFTDO) is incorporated into the proposed control strategy that enhances its robustness to the environmental disturbance. By fusion of neural network (NN) and minimal learning parameterization (MLP) techniques, the AFTDO is constructed without priori information about the ship model and the upper bound of disturbance. On the basis of undirected graph, the decentralized control law is developed with local information from neighboring USVs. Specially, since the AFTDO and the decentralized control law share the same set of NN, the whole algorithm is with merits of concise form and less adaptive parameters. Such design contributes to smaller computation load and facilitates the implementation of the algorithm in ocean engineering. The semi global finite-time uniformly boundedness (SGFTUB) of the closed-loop system is proved by the Lyapunov theory. Numerical simulations and comprehensive comparisons are conducted to demonstrate the remarkable performance and superiority of the proposed algorithm.
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