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Distributed Output Feedback Funnel Control for Uncertain Nonlinear Multiagent Systems.

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Title: Distributed Output Feedback Funnel Control for Uncertain Nonlinear Multiagent Systems.
Authors: Min, Xiao1 (AUTHOR) minxiao0420@163.com, Baldi, Simone1 (AUTHOR) S.Baldi@tudelft.nl, Yu, Wenwu1 (AUTHOR) wwyu@seu.edu.cn
Source: IEEE Transactions on Fuzzy Systems. Sep2022, Vol. 30 Issue 9, p3708-3721. 14p.
Subjects: Multiagent systems, Nonlinear systems, Adaptive fuzzy control, Uncertain systems, State feedback (Feedback control systems), Performance theory
Abstract: Adaptive output-feedback consensus with funnel performance is studied for nonlinear uncertain multiagent systems (MASs). The nonlinear MASs contain unknown dynamics and only an output variable can be measured. The other states are not measured directly and are reconstructed via fuzzy state observers. The presence of output feedback makes the proposed design significantly different from the existing literature on control with funnel performance. In particular, appropriate adaptive laws must be defined to handle the presence of uncertain dynamics and local output information from a few neighboring nodes. Interestingly, with a suitable error transformation, it is shown that the proposed control law has a simpler structure than barrier function methods proposed in the literature to handle funnel-like performance. With respect to this point, simulation studies illustrate that the proposed method can dramatically reduce the control effort while satisfying transient and steady-state performance imposed by the funnel. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Fuzzy Systems is the property of IEEE 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.)
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  Data: Distributed Output Feedback Funnel Control for Uncertain Nonlinear Multiagent Systems.
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  Data: <searchLink fieldCode="AR" term="%22Min%2C+Xiao%22">Min, Xiao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> minxiao0420@163.com</i><br /><searchLink fieldCode="AR" term="%22Baldi%2C+Simone%22">Baldi, Simone</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> S.Baldi@tudelft.nl</i><br /><searchLink fieldCode="AR" term="%22Yu%2C+Wenwu%22">Yu, Wenwu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wwyu@seu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Fuzzy+Systems%22">IEEE Transactions on Fuzzy Systems</searchLink>. Sep2022, Vol. 30 Issue 9, p3708-3721. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Multiagent+systems%22">Multiagent systems</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+systems%22">Nonlinear systems</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+fuzzy+control%22">Adaptive fuzzy control</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertain+systems%22">Uncertain systems</searchLink><br /><searchLink fieldCode="DE" term="%22State+feedback+%28Feedback+control+systems%29%22">State feedback (Feedback control systems)</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+theory%22">Performance theory</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Adaptive output-feedback consensus with funnel performance is studied for nonlinear uncertain multiagent systems (MASs). The nonlinear MASs contain unknown dynamics and only an output variable can be measured. The other states are not measured directly and are reconstructed via fuzzy state observers. The presence of output feedback makes the proposed design significantly different from the existing literature on control with funnel performance. In particular, appropriate adaptive laws must be defined to handle the presence of uncertain dynamics and local output information from a few neighboring nodes. Interestingly, with a suitable error transformation, it is shown that the proposed control law has a simpler structure than barrier function methods proposed in the literature to handle funnel-like performance. With respect to this point, simulation studies illustrate that the proposed method can dramatically reduce the control effort while satisfying transient and steady-state performance imposed by the funnel. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Fuzzy Systems is the property of IEEE 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:
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      – Type: doi
        Value: 10.1109/TFUZZ.2021.3126113
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 3708
    Subjects:
      – SubjectFull: Multiagent systems
        Type: general
      – SubjectFull: Nonlinear systems
        Type: general
      – SubjectFull: Adaptive fuzzy control
        Type: general
      – SubjectFull: Uncertain systems
        Type: general
      – SubjectFull: State feedback (Feedback control systems)
        Type: general
      – SubjectFull: Performance theory
        Type: general
    Titles:
      – TitleFull: Distributed Output Feedback Funnel Control for Uncertain Nonlinear Multiagent Systems.
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            NameFull: Min, Xiao
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            NameFull: Baldi, Simone
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            NameFull: Yu, Wenwu
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            – D: 01
              M: 09
              Text: Sep2022
              Type: published
              Y: 2022
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            – TitleFull: IEEE Transactions on Fuzzy Systems
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