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Bipartite output consensus in networked multi-agent systems of high-order power integrators with signed digraph and input noises

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  • Hongwen Ma
  • Derong Liu
  • Ding Wang
  • Biao Luo

Abstract

In this paper, we concentrate on investigating bipartite output consensus in networked multi-agent systems of high-order power integrators. Systems with power integrator are ubiquitous among weakly coupled, unstable and underactuated mechanical systems. In the presence of input noises, an adaptive disturbance compensator and a technique of adding power integrator are introduced to the complex nonlinear multi-agent systems to reduce the deterioration of system performance. Additionally, due to the existence of negative communication weights among agents, whether bipartite output consensus of high-order power integrators can be achieved remains unknown. Therefore, it is of great importance to study this issue. The underlying idea of designing the distributed controller is to combine the output information of each agent itself and its neighbours, the state feedback within its internal system and input adaptive noise compensator all together. When the signed digraph is structurally balanced, bipartite output consensus can be reached. Finally, numerical simulations are provided to verify the validity of the developed criteria.

Suggested Citation

  • Hongwen Ma & Derong Liu & Ding Wang & Biao Luo, 2016. "Bipartite output consensus in networked multi-agent systems of high-order power integrators with signed digraph and input noises," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(13), pages 3116-3131, October.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:13:p:3116-3131
    DOI: 10.1080/00207721.2015.1090039
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    1. Fenglan Sun & Zhi-Hong Guan & Li Ding & Yan-Wu Wang, 2013. "Mean square average-consensus for multi-agent systems with measurement noise and time delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(6), pages 995-1005.
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    Cited by:

    1. Peng, Zhinan & Hu, Jiangping & Shi, Kaibo & Luo, Rui & Huang, Rui & Ghosh, Bijoy Kumar & Huang, Jiuke, 2020. "A novel optimal bipartite consensus control scheme for unknown multi-agent systems via model-free reinforcement learning," Applied Mathematics and Computation, Elsevier, vol. 369(C).

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