Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems

Yibo Zhang; Dan Wang; Zhouhua Peng

doi:10.1007/978-3-319-70136-3_15

Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems

Yibo Zhang
, Dan Wang^*
, Zhouhua Peng

^*Corresponding author for this work

Department of Computer Science

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

In this paper, a consensus maneuvering problem is investigated for uncertain nonlinear systems in strict-feedback form. Consensus maneuvering controllers are developed based on a modular design approach. Specifically, an estimation module is proposed, where a neural network is employed for approximating the unknown nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method. Finally, the input-to-state stability of the close-loop system is analyzed via cascade theory, and the consensus maneuvering error is proved to converge to a residual set.

Original language	English
Pages (from-to)	139-146
Journal	Lecture Notes in Computer Science
Volume	10639
DOIs	https://doi.org/10.1007/978-3-319-70136-3_15
Publication status	Published - Nov 2017
Event	24th International Conference on Neural Information Processing (ICONIP 2017) - Guangzhou, China Duration: 14 Nov 2017 → 18 Nov 2017

Research Keywords

Consensus maneuvering
Modular design approach
Strict-Feedback system
Uncertain nonlinearity

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10.1007/978-3-319-70136-3_15

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title = "Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems",

abstract = "In this paper, a consensus maneuvering problem is investigated for uncertain nonlinear systems in strict-feedback form. Consensus maneuvering controllers are developed based on a modular design approach. Specifically, an estimation module is proposed, where a neural network is employed for approximating the unknown nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method. Finally, the input-to-state stability of the close-loop system is analyzed via cascade theory, and the consensus maneuvering error is proved to converge to a residual set.",

keywords = "Consensus maneuvering, Modular design approach, Strict-Feedback system, Uncertain nonlinearity",

author = "Yibo Zhang and Dan Wang and Zhouhua Peng",

year = "2017",

month = nov,

doi = "10.1007/978-3-319-70136-3\_15",

language = "English",

volume = "10639",

pages = "139--146",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

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note = "24th International Conference on Neural Information Processing (ICONIP 2017) ; Conference date: 14-11-2017 Through 18-11-2017",

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TY - JOUR

T1 - Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems

AU - Zhang, Yibo

AU - Wang, Dan

AU - Peng, Zhouhua

PY - 2017/11

Y1 - 2017/11

N2 - In this paper, a consensus maneuvering problem is investigated for uncertain nonlinear systems in strict-feedback form. Consensus maneuvering controllers are developed based on a modular design approach. Specifically, an estimation module is proposed, where a neural network is employed for approximating the unknown nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method. Finally, the input-to-state stability of the close-loop system is analyzed via cascade theory, and the consensus maneuvering error is proved to converge to a residual set.

AB - In this paper, a consensus maneuvering problem is investigated for uncertain nonlinear systems in strict-feedback form. Consensus maneuvering controllers are developed based on a modular design approach. Specifically, an estimation module is proposed, where a neural network is employed for approximating the unknown nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method. Finally, the input-to-state stability of the close-loop system is analyzed via cascade theory, and the consensus maneuvering error is proved to converge to a residual set.

KW - Consensus maneuvering

KW - Modular design approach

KW - Strict-Feedback system

KW - Uncertain nonlinearity

UR - https://www.scopus.com/pages/publications/85035149650

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85035149650&origin=recordpage

U2 - 10.1007/978-3-319-70136-3_15

DO - 10.1007/978-3-319-70136-3_15

M3 - RGC 21 - Publication in refereed journal

SN - 0302-9743

VL - 10639

SP - 139

EP - 146

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - 24th International Conference on Neural Information Processing (ICONIP 2017)

Y2 - 14 November 2017 through 18 November 2017

ER -

Consensus Maneuvering of Uncertain Nonlinear Strict-Feedback Systems

Abstract

Research Keywords

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