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Adaptive event-triggered consensus of multi-agent systems with spherical polar coordinate quantization mechanism

Author

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  • Cai, Jiayi
  • Xiao, Canrong
  • Wang, Jingyi
  • Feng, Jianwen
  • Gong, Huajun

Abstract

In this paper, the event-triggered consensus of multi-agent systems (MASs) with directed topology is investigated under both static and dynamic quantization strategies by applying the adaptive control framework. Firstly, a novel quantizer based on spherical polar coordinate is introduced to quantize high-dimensional vectors, aiming at addressing the bandwidth constraint on signal transmission and reducing the required number of quantizers and triggering times. Secondly, the time-varying coupling gain is incorporated into the control protocol, which enhances the flexibility of control parameter design and allows each agent to operate in a distributed manner. Furthermore, the designed event-triggered mechanism (ETM) consisting of controllers and quantizer parameters is adopted for the MASs to achieve bounded consensus under the static quantization strategy. By contrast, under the similar ETM and the proposed dynamic quantization strategy, it is possible for the states of all agents to asymptotical converge to a common state. Besides, it is also demonstrated that there is no occurrence of Zeno behavior for triggering time sequences under both quantization strategies. Finally, some numerical examples are discussed in numerical simulation to demonstrate the effectiveness of the proposed results.

Suggested Citation

  • Cai, Jiayi & Xiao, Canrong & Wang, Jingyi & Feng, Jianwen & Gong, Huajun, 2023. "Adaptive event-triggered consensus of multi-agent systems with spherical polar coordinate quantization mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    • Handle: RePEc:eee:phsmap:v:627:y:2023:i:c:s0378437123006970
    DOI: 10.1016/j.physa.2023.129142
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    Cited by:

    1. Zheng, Ying & Wu, Yayong & Jiang, Guo-Ping, 2024. "Exploring synchronizability of complex dynamical networks from edges perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).

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