Adaptive prescribed performance consensus tracking for uncertain delayed multiagent systems via command filtered output feedback.
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| Title: | Adaptive prescribed performance consensus tracking for uncertain delayed multiagent systems via command filtered output feedback. |
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| Authors: | Sun, Guofa1 (AUTHOR), Pan, Fengyang1 (AUTHOR) panfengyang1123@163.com, Liu, Qingxi1 (AUTHOR), Zheng, Jiaxin1 (AUTHOR) |
| Source: | International Journal of Systems Science. Augu2025, Vol. 56 Issue 11, p2517-2534. 18p. |
| Subjects: | Multiagent systems, Control theory (Engineering), Feedback control systems, Adaptive control systems, Simulation methods & models, Artificial neural networks |
| Abstract: | This article investigates the adaptive fixed-time prescribed performance (FTPP) consensus tracking control problem for uncertain nonstrict-feedback multiagent systems with unmeasured states and time-varying delays. First, a piecewise function is proposed to characterise FTPP and eliminate the initial value limitations present in traditional prescribed performance control methods. To ensure that tracking errors satisfy prescribed performance, barrier functions are further constructed and introduced into the control design process. Second, based on the approximation of neural networks, adaptive neural state observers are designed to estimate the unmeasured states. Then, an adaptive FTPP consensus control scheme is developed based on command filtered backstepping technique and Lyapunov-Krasovskii functional. It guarantees that (1) all signals in the closed-loop system are semiglobally uniformly ultimately bounded; and (2) for any bounded initial values, all followers' outputs can track the leader's output within a prescribed fixed-time and tracking accuracy, while satisfying the required transient tracking performance. Finally, the effectiveness of the proposed control scheme is verified through simulation studies. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186450393 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adaptive prescribed performance consensus tracking for uncertain delayed multiagent systems via command filtered output feedback. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sun%2C+Guofa%22">Sun, Guofa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Fengyang%22">Pan, Fengyang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> panfengyang1123@163.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Qingxi%22">Liu, Qingxi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Jiaxin%22">Zheng, Jiaxin</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Systems+Science%22">International Journal of Systems Science</searchLink>. Augu2025, Vol. 56 Issue 11, p2517-2534. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Multiagent+systems%22">Multiagent systems</searchLink><br /><searchLink fieldCode="DE" term="%22Control+theory+%28Engineering%29%22">Control theory (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+systems%22">Feedback control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This article investigates the adaptive fixed-time prescribed performance (FTPP) consensus tracking control problem for uncertain nonstrict-feedback multiagent systems with unmeasured states and time-varying delays. First, a piecewise function is proposed to characterise FTPP and eliminate the initial value limitations present in traditional prescribed performance control methods. To ensure that tracking errors satisfy prescribed performance, barrier functions are further constructed and introduced into the control design process. Second, based on the approximation of neural networks, adaptive neural state observers are designed to estimate the unmeasured states. Then, an adaptive FTPP consensus control scheme is developed based on command filtered backstepping technique and Lyapunov-Krasovskii functional. It guarantees that (1) all signals in the closed-loop system are semiglobally uniformly ultimately bounded; and (2) for any bounded initial values, all followers' outputs can track the leader's output within a prescribed fixed-time and tracking accuracy, while satisfying the required transient tracking performance. Finally, the effectiveness of the proposed control scheme is verified through simulation studies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00207721.2024.2449237 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 2517 Subjects: – SubjectFull: Multiagent systems Type: general – SubjectFull: Control theory (Engineering) Type: general – SubjectFull: Feedback control systems Type: general – SubjectFull: Adaptive control systems Type: general – SubjectFull: Simulation methods & models Type: general – SubjectFull: Artificial neural networks Type: general Titles: – TitleFull: Adaptive prescribed performance consensus tracking for uncertain delayed multiagent systems via command filtered output feedback. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sun, Guofa – PersonEntity: Name: NameFull: Pan, Fengyang – PersonEntity: Name: NameFull: Liu, Qingxi – PersonEntity: Name: NameFull: Zheng, Jiaxin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Augu2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00207721 Numbering: – Type: volume Value: 56 – Type: issue Value: 11 Titles: – TitleFull: International Journal of Systems Science Type: main |
| ResultId | 1 |
