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Dynamic Event-triggered Distributed Observer Based Output Regulation of Heterogeneous Multi-agent Systems

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  • Control Theory and Applications
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Abstract

In this paper, the output regulation problem for heterogeneous linear multi-agent systems is investigated, where each agent suffers from the detectability deficiency problem. Specifically, each agent has access to only partial output information of the exosystem, which bring about challenges to estimate full states of the exosystem. By using the observability decomposition technique, unobservable states in each agent are extracted. Then, a kind of distributed observer with dynamic event-triggered mechanism is developed to estimate full states of the exosystem for each agent cooperatively. Besides, the Zeno behavior is voided strictly when executing the event-triggered strategy. Furthermore, the distributed observer is employed to solve the output regulation problem of heterogeneous multi-agent systems based on the feedforward output regulation technique. Finally, a numerical example is conducted to verify the correctness of the proposed control algorithm.

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Author information

Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China

    Kairui Chen, Zhangmou Zhu & Jianhui Wang

  2. School of Computer & Information, Qiannan Normal University for Nationalities, Duyun, 558000, China

    Kairui Chen

  3. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510000, China

    Xianxian Zeng

  4. Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong, Shenzhen, 518000, China

    Xianxian Zeng

Authors
  1. Kairui Chen
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  2. Zhangmou Zhu
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Correspondence to Jianhui Wang.

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This work was supported in part by the National Natural Science Foundation of China under Grant 62103115, in part by the Natural Science Foundation of Guangdong Province under Grant 2021A1515011636, in part by the basic and applied basic research projects jointly funded by Guangzhou and schools (colleges) under Grant 202201020233, in part by the Open Research Fund from the Guangdong Provincial Key Laboratory of Big Data Computing, the Chinese University of Hong Kong, Shenzhen under Grant B10120210117-OF08 and in part by the Guangdong Province Ordinary Colleges and Universities Young Innovative Talents Project under Grant 2022KQNCX038.

Kairui Chen received his Ph.D. degree in control science and engineering from Guangdong University of Technology, Guangzhou, China, in 2017. He is currently an Associate Professor with the School of Mechanical and Electrical Engineering, Guangzhou University, and also with School of Computer & Information, Qiannan Normal University for Nationalities. His research interests include multi-agent system control, adaptive control, and distributed estimation.

Zhangmou Zhu received his bachelor’s degree from the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China, in 2020. He is currently pursuing a master’s degree in the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou. His research interests include multi-agent system control, adaptive dynamic programming, and optimal control.

Xianxian Zeng received his B.Eng. and Ph.D. degrees from the School of Automation, Guangdong University of Technology, Guangzhou, China, in 2015 and 2020, respectively. He is currently a Lecturer with the School of Computer Science, Guangdong Polytechnic Normal University. His research interests include computer vision, pattern recognition, and machine learning.

Jianhui Wang received his M.S. and Ph.D. degrees from the School of Automation, Guangdong University of Technology, Guangzhou, China, in 2009 and 2019, respectively. Since 2009, he has been with the School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou. He has won the title of the Yangcheng Scholars and Guangzhou Good Teacher. His current research interests include nonlinear systems, linear systems, and intelligent control.

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Chen, K., Zhu, Z., Zeng, X. et al. Dynamic Event-triggered Distributed Observer Based Output Regulation of Heterogeneous Multi-agent Systems. Int. J. Control Autom. Syst. 22, 1176–1185 (2024). https://doi.org/10.1007/s12555-023-0013-7

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