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Distributed formation control of fractional-order multi-agent systems with relative damping and communication delay

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Abstract

The distributed formation control of fractional-order multi-agent systems is mainly studied under directed communication graphs in this paper. Firstly, a control law with relative damping and communication delay are proposed. Then, some sufficient conditions for achieving formation control are derived using matrix theory, graph theory and the frequency domain analysis method. Finally, based on the numerical method of predictor-corrector, several simulations are presented to illustrate the effectiveness of the obtained results.

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Author information

Authors and Affiliations

  1. School of Mathematics and Physics, University of Science and Technology, Beijing, 100083, China

    Jing Bai

  2. Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, China

    Guoguang Wen & Yongguang Yu

  3. Weifang Engineering Vocational College, Weifang, 262500, China

    Yu Song

  4. CRIStAL, UMR CNRS 9189, Ecole Centrale de Lille, Villeneuve d’Ascq, 59650, France

    Ahmed Rahmani

Authors
  1. Jing Bai
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  2. Guoguang Wen
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  3. Yu Song
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  4. Ahmed Rahmani
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  5. Yongguang Yu
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Corresponding author

Correspondence to Guoguang Wen.

Additional information

Recommended by Associate Editor Ho Jae Lee under the direction of Editor Yoshito Ohta. This work was supported by the Fundamental Research Funds for the Central Universities [Grant number FRF-TP-16-011A1]; The National Natural Science Foundation of China under Grants 61403019 and 11371049.

Jing Bai received the B.S. degree and master degree at the Department of Mathematical Science, Beijing jiaotong University, China in 2010 and 2012, and the Ph.D. degree at CRIStAL, Ecole Centrale de Lille, France in 2015. She is currently working at School of Mathematics and Physics, University of Science and Technology, Beijing, China. Her research interest focuses on formation control of multi-agent systems, consensus of multi-agent, Chaos control and synchronization.

Guoguang Wen received the B.S. degree at the Department of Mathematical Science, Inner Mongolia University, China in 2007, the M.S. degree at the Department of Mathematics, School of Science, Beijing Jiaotong University, China in 2009, and the Ph.D. degree at CRIStAL, Ecole Centrale de Lille, France, in 2012. Currently, he is working at the Department of Mathematics, School of Science, and Beijing Jiaotong University, China. His research interest focuses on cooperative control for multi-agent systems, control of multi-robots formation, nonlinear dynamics and control, neural networks.

Yu Song received the master degree at the Department of Mathematical Science, Beijing jiaotong University, China in 2012. He is currently working at Weifang Engineering Vocational College, Weifang, China. His research interest focuses on systems control, Chaos control and Lorenz-84.

Ahmed Rahmani received his Ph.D. degree in Automatic Control Engineering and Computer Science from Lille University of Technology and Ecole Centrale de Lille, France in 1993. He is a full professor at Ecole Centrale de Lille now. His current research interests are in graphic methods and tools for analysis and control of complex systems: application to mobile robotics and intelligent transport.

Yongguang Yu received his MS degree at the Department of Mathematical Science, Inner Mongolia University, China in 2001, and the PhD degree in Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, China in 2004. From 2007 to 2009, he was a Research Fellow in City University of Hong Kong, China. Since 2010, he has been a Professor at the Department of Mathematics, School of Science, and Beijing Jiaotong University, China. His research interests include chaotic dynamics, Chaos control and synchronization, complex networks, nonlinear control and multi-agent systems.

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Bai, J., Wen, G., Song, Y. et al. Distributed formation control of fractional-order multi-agent systems with relative damping and communication delay. Int. J. Control Autom. Syst. 15, 85–94 (2017). https://doi.org/10.1007/s12555-015-0132-x

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  • DOI: https://doi.org/10.1007/s12555-015-0132-x

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