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Sample-based Dynamic Event-triggered Algorithm for Optimization Problem of Multi-agent Systems

  • Control Theory and Applications
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Abstract

The convex optimization problem of multi-agent systems is investigated. In order to deduce the communication burden of the system and simplify the implementation of the algorithm on the digital controllers, a sample-based event-triggered optimization algorithm is proposed and a novel dynamic event-trigged condition is designed. The global optimal solution can be obtained exponentially. The event-triggered time intervals are significantly enlarged by dynamic event-triggered condition. Moreover, Zeno behavior is excluded due to sampling control mechanism in our scheme. Two numerical cases are presented to validate the relevant results.

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Authors and Affiliations

  1. Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), College of Automation, and College of Mathematics and Statistics, Nanjing University of Information Science & Technology, Jiangsu, 210044, China

    Zhongyuan Zhao

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  1. Zhongyuan Zhao
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Correspondence to Zhongyuan Zhao.

Additional information

This research was supported by Natural Science Foundation of Jiangsu Province (grant number BK20200824) and Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology (grant number 2019r082).

Zhongyuan Zhao received his Ph.D. degree from Chongqing University, Chongqing, China, in 2019. He is currently a lecturer with the College of Automation, and a postdoctor with the College of Mathematics and Statistics, Nanjing University of Information Science and Technology. His research interests include cooperative control, event triggered control, and distributed optimization.

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Zhao, Z. Sample-based Dynamic Event-triggered Algorithm for Optimization Problem of Multi-agent Systems. Int. J. Control Autom. Syst. 20, 2492–2502 (2022). https://doi.org/10.1007/s12555-021-0157-2

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  • DOI: https://doi.org/10.1007/s12555-021-0157-2

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