基于全状态约束的水下打捞器自适应轨迹跟踪控制

IF 1.4 4区计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS

Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering Pub Date : 2024-07-25 DOI:10.1177/09596518241262503

Wenyi Tan, Yan Zhang, Qiang Zhang, Yancai Hu, Yang Liu

{"title":"基于全状态约束的水下打捞器自适应轨迹跟踪控制","authors":"Wenyi Tan, Yan Zhang, Qiang Zhang, Yancai Hu, Yang Liu","doi":"10.1177/09596518241262503","DOIUrl":null,"url":null,"abstract":"Aiming at the trajectory tracking control problem of underwater salvage vehicle affected by dynamic uncertainty and external disturbance, a trajectory tracking control scheme based on full-state constraint is proposed. Firstly, radial basis function neural network (RBFNN) and adaptive virtual parameter learning method are combined to compensate dynamic uncertainty and external interference. Then barrier Lyapunov function (BLF) is used to prevent the violation of the full-state constraint. The Lyapunov stability theory is used to prove that the proposed control scheme can achieve semi-global uniform boundedness of the closed-loop system. Finally, simulation results further demonstrate its excellent performance. The proposed control scheme has good reference value for the application of the underwater salvage vehicle in practical engineering.","PeriodicalId":20638,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering","volume":"71 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive trajectory tracking control of underwater salvage vehicle based on full-state constraint\",\"authors\":\"Wenyi Tan, Yan Zhang, Qiang Zhang, Yancai Hu, Yang Liu\",\"doi\":\"10.1177/09596518241262503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the trajectory tracking control problem of underwater salvage vehicle affected by dynamic uncertainty and external disturbance, a trajectory tracking control scheme based on full-state constraint is proposed. Firstly, radial basis function neural network (RBFNN) and adaptive virtual parameter learning method are combined to compensate dynamic uncertainty and external interference. Then barrier Lyapunov function (BLF) is used to prevent the violation of the full-state constraint. The Lyapunov stability theory is used to prove that the proposed control scheme can achieve semi-global uniform boundedness of the closed-loop system. Finally, simulation results further demonstrate its excellent performance. The proposed control scheme has good reference value for the application of the underwater salvage vehicle in practical engineering.\",\"PeriodicalId\":20638,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering\",\"volume\":\"71 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1177/09596518241262503\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/09596518241262503","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 0

摘要

针对水下打捞船受动态不确定性和外部干扰影响的轨迹跟踪控制问题，提出了一种基于全状态约束的轨迹跟踪控制方案。首先，结合径向基函数神经网络（RBFNN）和自适应虚拟参数学习方法来补偿动态不确定性和外部干扰。然后使用障壁李亚普诺夫函数（BLF）来防止违反全状态约束。利用 Lyapunov 稳定性理论证明了所提出的控制方案可以实现闭环系统的半全局均匀有界性。最后，仿真结果进一步证明了其卓越的性能。提出的控制方案对水下打捞器在实际工程中的应用具有很好的参考价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Adaptive trajectory tracking control of underwater salvage vehicle based on full-state constraint

Aiming at the trajectory tracking control problem of underwater salvage vehicle affected by dynamic uncertainty and external disturbance, a trajectory tracking control scheme based on full-state constraint is proposed. Firstly, radial basis function neural network (RBFNN) and adaptive virtual parameter learning method are combined to compensate dynamic uncertainty and external interference. Then barrier Lyapunov function (BLF) is used to prevent the violation of the full-state constraint. The Lyapunov stability theory is used to prove that the proposed control scheme can achieve semi-global uniform boundedness of the closed-loop system. Finally, simulation results further demonstrate its excellent performance. The proposed control scheme has good reference value for the application of the underwater salvage vehicle in practical engineering.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 工程技术-自动化与控制系统

CiteScore

3.50

自引率

18.80%

发文量

审稿时长

4.2 months

期刊介绍： Systems and control studies provide a unifying framework for a wide range of engineering disciplines and industrial applications. The Journal of Systems and Control Engineering refleSystems and control studies provide a unifying framework for a wide range of engineering disciplines and industrial applications. The Journal of Systems and Control Engineering reflects this diversity by giving prominence to experimental application and industrial studies. "It is clear from the feedback we receive that the Journal is now recognised as one of the leaders in its field. We are particularly interested in highlighting experimental applications and industrial studies, but also new theoretical developments which are likely to provide the foundation for future applications. In 2009, we launched a new Series of "Forward Look" papers written by leading researchers and practitioners. These short articles are intended to be provocative and help to set the agenda for future developments. We continue to strive for fast decision times and minimum delays in the production processes." Professor Cliff Burrows - University of Bath, UK This journal is a member of the Committee on Publication Ethics (COPE).cts this diversity by giving prominence to experimental application and industrial studies.