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A Game-theoretical Approach for a Finite-time Consensus of Second-order Multi-agent System

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  • Control Theory and Applications
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Abstract

The second-order consensus problem depends on not only the topology condition but also the coupling strength of the relative positions and velocities between neighboring agents. This paper seeks to solve the finite-time consensus problem of second-order multi-agent systems by games with special structures. Potential game and weakly acyclic game were applied for modeling the second-order consensus problem with different topologies. Furthermore, this paper introduces the event-triggered asynchronous cellular learning automata algorithm for optimizing the decision making process of the agents, which facilitates a convergence with the Nash equilibrium. Finally, numerical examples illustrate the effectiveness of the models.

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Authors and Affiliations

  1. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University, Nanjing, 210096, China

    Lei Xue & Changyin Sun

  2. Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, 65409, USA

    Donald C. Wunsch II

Authors
  1. Lei Xue
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  2. Changyin Sun
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  3. Donald C. Wunsch II
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Corresponding author

Correspondence to Changyin Sun.

Additional information

Recommended by Associate Editor Juhoon Back under the direction of Editor Yoshito Ohta. This research was supported by the National Natural Science Foundation of China under grants 61806052, by the Natural Science Foundation of Jiangsu Province of China under grants BK20180361, and by the Fundamental Research Funds for the Central Universities. Partial support for this research was received from the Missouri University of Science and Technology Intelligent Systems Center, the Mary K. Finley Missouri Endowment, the Lifelong Learning Machines program from DARPA/Microsystems Technology Office, and the Army Research Laboratory (ARL); and it was accomplished under Cooperative Agreement Number W911NF-18-2-0260. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

Lei Xue received his Ph.D. degree in control science and engineering from Southeast University, Nanjing, China, in 2017. From September 2013 to September 2014, he was a Visiting Ph.D. student with Applied Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USA. Currently he is a Postdoctoral with School of Automation, Southeast University, Nanjing, China. His research interests include game theory, multi-agent system, and optimization control.

Changyin Sun is a professor in School of Automation, Southeast University, Nanjing, China. He received his Bachelor Degree in College of Mathematics, Sichuan University, China, and his M.S. and Ph.D. degrees in Electrical Engineering from the Southeast University, Nanjing, China, respectively, in 2001 and 2004. He is the Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE/CAA Journal of Automatica Sinica. His research interests include intelligent control, flight control, pattern recognition, optimal theory, etc.

Donald C. Wunsch II is the Mary K. Finley Missouri Distinguished Professor at Missouri University of Science and Technology. He received his B.S. and M.S. degrees from University of New Mexico and University of Washington, USA, respectively. He received his Ph.D. degree from University of Washington (Seattle), USA. Key research contributions are: Clustering / Unsupervised Learning; Adaptive Resonance and Reinforcement Learning architectures, hardware and applications; Neurofuzzy regression; Traveling Salesman Problem heuristics; Robotic Swarms; and Bioinformatics. He is an IEEE Fellow and previous INNS President, INNS Fellow and Senior Fellow 2007–2013, NSF CAREER Award winner, and winner of the 2015 INNS Gabor Award. He served as IJCNN General Chair, and on several Boards, including the St. Patrick’s School Board, IEEE Neural Networks Council, International Neural Networks Society, and the University of Missouri Bioinformatics Consortium, Chaired the Missouri University of Science and Technology Information Technology and Computing Committee as well as the Student Design and Experiential Learning Center Board.

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Xue, L., Sun, C. & Wunsch, D.C. A Game-theoretical Approach for a Finite-time Consensus of Second-order Multi-agent System. Int. J. Control Autom. Syst. 17, 1071–1083 (2019). https://doi.org/10.1007/s12555-017-0716-8

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  • DOI: https://doi.org/10.1007/s12555-017-0716-8

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