Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization

This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust cont...

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Autores principales:	Kunyi Jiang, Lei Mao, Yumin Su, Yuxin Zheng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	underactuated USV prescribed performance control input quantization model-free control minimum learning parameter Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/e42e0d4329e94220af4dd77a6e9042f4
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id	oai:doaj.org-article:e42e0d4329e94220af4dd77a6e9042f4
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spelling	oai:doaj.org-article:e42e0d4329e94220af4dd77a6e9042f42021-11-25T19:07:36ZTrajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization10.3390/sym131122082073-8994https://doaj.org/article/e42e0d4329e94220af4dd77a6e9042f42021-11-01T00:00:00Zhttps://www.mdpi.com/2073-8994/13/11/2208https://doaj.org/toc/2073-8994This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated for surge motion and yaw motion. To guarantee the prespecified performance requirements for position tracking control, the constrained error dynamics are transformed to unconstrained ones by virtue of a tangent-type nonlinear mapping function. On the other hand, the inaccurate model can be identified through radial basis neural networks (RBFNNs), where the minimum learning parameter (MLP) algorithm is employed with a low computational complexity. Furthermore, quantization errors can be effectively reduced even when the parameters of the quantizer remain unavailable to designers. Finally, the effectiveness of the proposed controllers is verified via theoretical analyses and numerical simulations.Kunyi JiangLei MaoYumin SuYuxin ZhengMDPI AGarticleunderactuated USVprescribed performance controlinput quantizationmodel-free controlminimum learning parameterMathematicsQA1-939ENSymmetry, Vol 13, Iss 2208, p 2208 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	underactuated USV prescribed performance control input quantization model-free control minimum learning parameter Mathematics QA1-939
spellingShingle	underactuated USV prescribed performance control input quantization model-free control minimum learning parameter Mathematics QA1-939 Kunyi Jiang Lei Mao Yumin Su Yuxin Zheng Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
description	This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated for surge motion and yaw motion. To guarantee the prespecified performance requirements for position tracking control, the constrained error dynamics are transformed to unconstrained ones by virtue of a tangent-type nonlinear mapping function. On the other hand, the inaccurate model can be identified through radial basis neural networks (RBFNNs), where the minimum learning parameter (MLP) algorithm is employed with a low computational complexity. Furthermore, quantization errors can be effectively reduced even when the parameters of the quantizer remain unavailable to designers. Finally, the effectiveness of the proposed controllers is verified via theoretical analyses and numerical simulations.
format	article
author	Kunyi Jiang Lei Mao Yumin Su Yuxin Zheng
author_facet	Kunyi Jiang Lei Mao Yumin Su Yuxin Zheng
author_sort	Kunyi Jiang
title	Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
title_short	Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
title_full	Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
title_fullStr	Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
title_full_unstemmed	Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
title_sort	trajectory tracking control for underactuated usv with prescribed performance and input quantization
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e42e0d4329e94220af4dd77a6e9042f4
work_keys_str_mv	AT kunyijiang trajectorytrackingcontrolforunderactuatedusvwithprescribedperformanceandinputquantization AT leimao trajectorytrackingcontrolforunderactuatedusvwithprescribedperformanceandinputquantization AT yuminsu trajectorytrackingcontrolforunderactuatedusvwithprescribedperformanceandinputquantization AT yuxinzheng trajectorytrackingcontrolforunderactuatedusvwithprescribedperformanceandinputquantization
_version_	1718410311622459392

Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization

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