Nussbaum-Based Distributed Containment Control for Nonlinear Multiagent Systems With Quantized Inputs

This article explores the distributed containment control problem for uncertain nonlinear multiagent systems subject to external disturbances and input quantization, where the constant control gains and the upper bounds of the external disturbances are unknown. First, the reference generator is cons...

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Published inIEEE transactions on control of network systems Vol. 12; no. 2; pp. 1290 - 1299
Main Authors Liu, Yang, Zhang, Jiaming
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.06.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN2325-5870
2372-2533
DOI10.1109/TCNS.2024.3510573

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Abstract This article explores the distributed containment control problem for uncertain nonlinear multiagent systems subject to external disturbances and input quantization, where the constant control gains and the upper bounds of the external disturbances are unknown. First, the reference generator is constructed for each follower agent to generate the virtual tracking signal, confining to the convex hull spanned by the leaders. Meanwhile, the unmeasurable state variable of each follower is estimated by adopting the <inline-formula><tex-math notation="LaTeX">K</tex-math></inline-formula>-filters based on the available output/input signals and known system function matrices. Then, a distributed adaptive output feedback controller with only one updating parameter is designed for each follower by introducing a logarithmic quantization to quantize the control inputs under the framework of prescribed performance control. The lack of a priori knowledge for the control gain and the quantization gain is counteracted effectively by employing the Nussbaum function method in the adaptive backstepping design process. It is proved that the outputs of followers can enter into the convex hull of multiple leaders and the relevant tracking errors satisfy the prescribed performance index. Finally, the validity of the proposed schemes is illustrated through simulation studies on robotic systems.
AbstractList This article explores the distributed containment control problem for uncertain nonlinear multiagent systems subject to external disturbances and input quantization, where the constant control gains and the upper bounds of the external disturbances are unknown. First, the reference generator is constructed for each follower agent to generate the virtual tracking signal, confining to the convex hull spanned by the leaders. Meanwhile, the unmeasurable state variable of each follower is estimated by adopting the [Formula Omitted]-filters based on the available output/input signals and known system function matrices. Then, a distributed adaptive output feedback controller with only one updating parameter is designed for each follower by introducing a logarithmic quantization to quantize the control inputs under the framework of prescribed performance control. The lack of a priori knowledge for the control gain and the quantization gain is counteracted effectively by employing the Nussbaum function method in the adaptive backstepping design process. It is proved that the outputs of followers can enter into the convex hull of multiple leaders and the relevant tracking errors satisfy the prescribed performance index. Finally, the validity of the proposed schemes is illustrated through simulation studies on robotic systems.
This article explores the distributed containment control problem for uncertain nonlinear multiagent systems subject to external disturbances and input quantization, where the constant control gains and the upper bounds of the external disturbances are unknown. First, the reference generator is constructed for each follower agent to generate the virtual tracking signal, confining to the convex hull spanned by the leaders. Meanwhile, the unmeasurable state variable of each follower is estimated by adopting the <inline-formula><tex-math notation="LaTeX">K</tex-math></inline-formula>-filters based on the available output/input signals and known system function matrices. Then, a distributed adaptive output feedback controller with only one updating parameter is designed for each follower by introducing a logarithmic quantization to quantize the control inputs under the framework of prescribed performance control. The lack of a priori knowledge for the control gain and the quantization gain is counteracted effectively by employing the Nussbaum function method in the adaptive backstepping design process. It is proved that the outputs of followers can enter into the convex hull of multiple leaders and the relevant tracking errors satisfy the prescribed performance index. Finally, the validity of the proposed schemes is illustrated through simulation studies on robotic systems.
Author Zhang, Jiaming
Liu, Yang
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Cites_doi 10.1016/j.ins.2022.08.096
10.1109/TSMC.2023.3292287
10.1080/00207721.2021.1975848
10.1109/TAC.2015.2508741
10.1016/j.automatica.2023.111100
10.1109/TCNS.2020.2972601
10.1109/TCNS.2022.3140684
10.1109/TSMCB.2003.817055
10.1109/TCNS.2014.2357531
10.1142/S2301385023410030
10.1007/s11633-016-1004-4
10.1016/j.isatra.2019.02.004
10.1016/j.isatra.2023.01.008
10.1109/TFUZZ.2015.2486817
10.1109/TAC.2021.3089626
10.1109/TCNS.2023.3235425
10.1109/TAC.2003.815049
10.1016/j.automatica.2017.12.008
10.1016/j.automatica.2022.110456
10.1109/TCNS.2022.3220705
10.1016/j.ins.2020.02.005
10.1016/j.ecolmodel.2003.06.006
10.1016/j.automatica.2018.09.034
10.1109/TAC.2016.2628204
10.1109/TCSII.2024.3367180
10.1109/TCYB.2020.2970454
10.1109/TSIPN.2023.3264992
10.1016/j.automatica.2014.10.079
10.1109/TAC.2013.2293452
10.1109/TAC.2020.3012027
10.1109/TSP.2022.3175020
10.1002/rnc.3274
10.1109/LCSYS.2022.3232305
10.1109/TRO.2024.3354161
10.1007/s11768-023-00174-7
10.1016/j.automatica.2013.07.016
10.1142/S2737480723500152
10.1016/0167-6911(83)90021-X
10.1016/j.automatica.2021.109545
10.1109/TCSI.2021.3121809
10.1109/TNNLS.2022.3230508
10.1080/00207721.2020.1849864
10.1109/TCNS.2019.2945676
10.1109/TCYB.2018.2817610
10.1109/TCNS.2015.2489338
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References ref13
ref35
ref12
ref34
ref15
ref37
ref14
ref36
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref39
ref16
ref38
ref19
ref18
ref24
ref23
ref45
ref26
ref25
ref20
ref42
ref41
ref22
ref44
ref21
ref43
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
References_xml – ident: ref1
  doi: 10.1016/j.ins.2022.08.096
– ident: ref20
  doi: 10.1109/TSMC.2023.3292287
– ident: ref39
  doi: 10.1080/00207721.2021.1975848
– ident: ref42
  doi: 10.1109/TAC.2015.2508741
– ident: ref10
  doi: 10.1016/j.automatica.2023.111100
– ident: ref8
  doi: 10.1109/TCNS.2020.2972601
– ident: ref18
  doi: 10.1109/TCNS.2022.3140684
– ident: ref25
  doi: 10.1109/TSMCB.2003.817055
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  doi: 10.1109/TCNS.2014.2357531
– ident: ref2
  doi: 10.1142/S2301385023410030
– ident: ref4
  doi: 10.1007/s11633-016-1004-4
– ident: ref12
  doi: 10.1016/j.isatra.2019.02.004
– ident: ref16
  doi: 10.1016/j.isatra.2023.01.008
– ident: ref29
  doi: 10.1109/TFUZZ.2015.2486817
– ident: ref43
  doi: 10.1109/TAC.2021.3089626
– ident: ref7
  doi: 10.1109/TCNS.2023.3235425
– ident: ref21
  doi: 10.1109/TAC.2003.815049
– ident: ref24
  doi: 10.1016/j.automatica.2017.12.008
– ident: ref5
  doi: 10.1016/j.automatica.2022.110456
– ident: ref9
  doi: 10.1109/TCNS.2022.3220705
– ident: ref23
  doi: 10.1016/j.ins.2020.02.005
– ident: ref3
  doi: 10.1016/j.ecolmodel.2003.06.006
– ident: ref22
  doi: 10.1016/j.automatica.2018.09.034
– ident: ref44
  doi: 10.1109/TAC.2016.2628204
– ident: ref34
  doi: 10.1109/TCSII.2024.3367180
– ident: ref17
  doi: 10.1109/TCYB.2020.2970454
– ident: ref6
  doi: 10.1109/TSIPN.2023.3264992
– ident: ref28
  doi: 10.1016/j.automatica.2014.10.079
– ident: ref45
  doi: 10.1109/TAC.2013.2293452
– ident: ref41
  doi: 10.1109/TAC.2020.3012027
– ident: ref11
  doi: 10.1109/TSP.2022.3175020
– ident: ref15
  doi: 10.1002/rnc.3274
– ident: ref37
  doi: 10.1109/LCSYS.2022.3232305
– ident: ref38
  doi: 10.1109/TRO.2024.3354161
– ident: ref35
  doi: 10.1007/s11768-023-00174-7
– ident: ref31
  doi: 10.1016/j.automatica.2013.07.016
– ident: ref36
  doi: 10.1142/S2737480723500152
– ident: ref27
  doi: 10.1016/0167-6911(83)90021-X
– ident: ref33
  doi: 10.1016/j.automatica.2021.109545
– ident: ref32
  doi: 10.1109/TCSI.2021.3121809
– ident: ref30
  doi: 10.1109/TNNLS.2022.3230508
– ident: ref40
  doi: 10.1080/00207721.2020.1849864
– ident: ref26
  doi: 10.1109/TCNS.2019.2945676
– ident: ref14
  doi: 10.1109/TCYB.2018.2817610
– ident: ref19
  doi: 10.1109/TCNS.2015.2489338
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Snippet This article explores the distributed containment control problem for uncertain nonlinear multiagent systems subject to external disturbances and input...
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SubjectTerms Accuracy
Containment
Containment control
Control systems
Convexity
Disturbances
Feedback control
Generators
input quantization
Multi-agent systems
Multiagent systems
Network systems
Nonlinear control
Nonlinear systems
Nussbaum function
Observers
Output feedback
Performance indices
prescribed performance
Quantization (signal)
Tracking errors
uncertain nonlinear systems
Upper bound
Upper bounds
Vectors
Title Nussbaum-Based Distributed Containment Control for Nonlinear Multiagent Systems With Quantized Inputs
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