期刊
AIMS MATHEMATICS
卷 5, 期 1, 页码 587-602出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2020039
关键词
platoon control; marine surface vessels; adaptive neural network control; barrier Lyapunov function; input saturation
资金
- Liaoning Province Natural Science Foundation [20170520430]
- Fundamental Research Funds for the Central Universities [3132018253]
This paper addresses the decentralized problem for marine surface vessels (MSVs) in the presence of unknown unmodeled nonlinear dynamics, time-varying external disturbances and input saturations. First, platoon formation is proceeded by using line-of-sight (LOS) guidance. Since each marine vehicle can only acquire information from its immediate predecessor, a symmetric barrier Lyapunov function (BLF) is employed to guarantee the formation errors constrained within a certain range such that leaders and followers can preserve the predefined information structure and ensure the correct steady-state regime. Next, due to the superior approximation capability of an adaptive neural network (NN), we propose a BLF-based controller to deal with the model uncertainties. Further, an auxiliary design system is introduced to compensate for the e ffect of input saturation. Finally, the uniform ultimate boundedness of all the state errors can be proved and simulation examples are presented to illustrate the e ffectiveness of the proposed method.
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