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Bipartite Containment Control for Multi-agent Systems Under Fixed and Markov Switching Topologies

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  • Intelligent Control and Applications
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Abstract

The distributed bipartite containment control problem of a set of general linear multi-agent systems with structural balanced symbolic graph is studied. The containment control analysis of communication topology under fixed topology and Markov switching topologies are given. Different from the traditional multi-agent containment control, a distributed observer and bipartite containment protocol are designed based on relative neighbour information. Algebraic graph theory and Lyapunov stability theory are applied to make the bipartite containment error and estimation error converge to zero under the action of the containment control protocol, thus making follower agents converge asymptotically to the states of leader agents. Finally, the effectiveness of the theoretical method is verified by simulation examples.

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Authors and Affiliations

  1. College of Information Sciences and Technology, Donghua University, 300 Wenhui Road, Songjiang District, Shanghai, 201620, China

    Xuan Gu, Wuneng Zhou, You Wu, Wanpeng Wu & Guang Yang

  2. Engineering Research Center of Digitized Textile and Fashion Technology, Donghua University, 300 Wenhui Road, Songjiang District, Shanghai, 201620, China

    Wuneng Zhou

Authors
  1. Xuan Gu
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  2. Wuneng Zhou
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  3. You Wu
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  4. Wanpeng Wu
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  5. Guang Yang
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Corresponding author

Correspondence to Wuneng Zhou.

Additional information

Xuan Gu is working toward an M.S. degree at Donghua University, Shanghai, China. Her current research interests include multiagent system stability analysis, adaptive control, and containment control.

Wuneng Zhou received his B.S. degree in mathematics from Huazhong Normal University, Hubei, China, in 1982, and a Ph.D. degree in control science and engineering from Zhejiang University, Zhejiang, China, in 2005. He is currently a Professor with Donghua University, Shanghai, China. His current research interests include stability, synchronization, and control for neural networks, multiagent system stability analysis, and formation control.

You Wu is working toward an M.S. degree at Donghua University, Shanghai, China. Her current research interests include fault diagnosis, deep learning, and multiagent system.

Wanpeng Wu is working toward an M.S. degree at Donghua University, Shanghai, China. His current research interests include traffic flow forecasting, deep learning, multiagent, and time series analysis.

Guang Yang is working toward an M.S. degree at Donghua University, Shanghai, China. His current research interests include deep learning, multiagent, traffic flow forecasting, and time series analysis.

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This work is supported by the Natural Science Foundation of Shanghai under grant no. 20ZR1402800.

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Gu, X., Zhou, W., Wu, Y. et al. Bipartite Containment Control for Multi-agent Systems Under Fixed and Markov Switching Topologies. Int. J. Control Autom. Syst. 21, 1331–1337 (2023). https://doi.org/10.1007/s12555-022-0027-6

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  • DOI: https://doi.org/10.1007/s12555-022-0027-6

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