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Title: Prescribed performance control of underactuated surface vessels' trajectory using a neural network and integral time-delay sliding mode (English)
Author: Chen, Yun
Author: Chen, Hua
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 59
Issue: 2
Year: 2023
Pages: 273-293
Summary lang: English
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Category: math
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Summary: To tackle the underactuated surface vessel (USV) trajectory tracking challenge with input delays and composite disturbances, an integral time-delay sliding mode controller based on backstepping is discussed. First, the law of virtual velocity control is established by coordinate transformation and the position error is caused to converge utilizing the performance function. At the same time, based on the estimation of velocity vector by the high-gain observer (HGO), radial basis function (RBF) neural network is applied to compensate for both the uncertainty of model parameters and external disturbances. The longitudinal and heading control laws are presented in combination with the integral time-delay sliding mode control. Then, on the basis of Lyapunov - Krasovskii functional and stability proof, virtual velocity error is guaranteed to converge to 0 in finite time. Finally, the outcomes of the numerical simulation demonstrate the reliability and efficiency of the proposed approach. (English)
Keyword: underactuated surface vessels
Keyword: trajectory tracking
Keyword: time-delay
Keyword: external disturbances
Keyword: sliding mode
Keyword: backstepping
Keyword: radial basis function(RBF)
MSC: 93A30
MSC: 93Dxx
idMR: MR4600378
DOI: 10.14736/kyb-2023-2-0273
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Date available: 2023-06-19T09:08:51Z
Last updated: 2023-08-04
Stable URL: http://hdl.handle.net/10338.dmlcz/151696
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