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H∞ sliding mode based scaled consensus control for linear multi-agent systems with disturbances

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  • Zhao, Lin
  • Jia, Yingmin
  • Yu, Jinpeng
  • Du, Junping

Abstract

This paper studies the scaled consensus control problem of networked multi-agent systems with linear coupling dynamics and external disturbances. A state feedback based distributed H∞ sliding mode control (SMC) approach is firstly established by designing integral-type sliding function, and a linear matrix inequality (LMI) based sufficient condition is given, which can guarantee the states of all agents achieving scaled consensus with H∞ disturbance attenuation index on sliding surface. A distributed adaptive SMC law with adaptive updated law is proposed such that the sliding surface is reachable. Then, the output feedback based distributed H∞ SMC is considered by designing distributed observer, and a SMC law is synthesized for the reaching motion based on the state estimates. A LMI based sufficient condition for the scaled consensus with H∞ disturbance attenuation index of the overall closed-loop system is derived. At last, the proposed distributed H∞ SMC is further extended to solve the scaled consensus control problem of networked multi-agent systems under switching topology. An example is included to show the effectiveness of the proposed methods.

Suggested Citation

  • Zhao, Lin & Jia, Yingmin & Yu, Jinpeng & Du, Junping, 2017. "H∞ sliding mode based scaled consensus control for linear multi-agent systems with disturbances," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 375-389.
    • Handle: RePEc:eee:apmaco:v:292:y:2017:i:c:p:375-389
    DOI: 10.1016/j.amc.2016.08.002
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    References listed on IDEAS

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    1. Lin Zhao & Yingmin Jia, 2016. "Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(8), pages 1931-1942, June.
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    6. He, Xiaoyan & Wang, Qingyun & Yu, Wenwu, 2015. "Distributed finite-time containment control for second-order nonlinear multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 509-521.
    7. Li, Jinsha & Li, Junmin, 2015. "Iterative learning control approach for a kind of heterogeneous multi-agent systems with distributed initial state learning," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 1044-1057.
    8. Feng, Tao & Zhang, Huaguang & Luo, Yanhong & Liang, Hongjing, 2015. "Consensus rate regulation for general linear multi-agent systems under directed topology," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 845-859.
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    Cited by:

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    5. Zhang, Yanhui & Liang, Hongjing & Ma, Hui & Zhou, Qi & Yu, Zhandong, 2018. "Distributed adaptive consensus tracking control for nonlinear multi-agent systems with state constraints," Applied Mathematics and Computation, Elsevier, vol. 326(C), pages 16-32.
    6. Li, Hongjie & Zhu, Yinglian & jing, Liu & ying, Wang, 2018. "Consensus of second-order delayed nonlinear multi-agent systems via node-based distributed adaptive completely intermittent protocols," Applied Mathematics and Computation, Elsevier, vol. 326(C), pages 1-15.
    7. Wang, Jinhuan & Xu, Yuling & Xu, Yong & Yang, Dedong, 2019. "Time-varying formation for high-order multi-agent systems with external disturbances by event-triggered integral sliding mode control," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 333-343.

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