IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v178y2024ics0960077923012808.html
   My bibliography  Save this article

Control costs of long-range interacting multi-agent systems with noise perturbation

Author

Listed:
  • Yin, Xiangxin
  • Dai, Haifeng
  • Zhao, Lingzhi
  • Zhao, Donghua
  • Xiao, Rui
  • Sun, Yongzheng

Abstract

As an important stage of collective dynamics, consensus is widespread in real-world moving groups, where one of the long-term challenges is to optimize the control costs of reaching consensus. However, current research on the consensus of multi-agents systems (MASs) usually only considers direct interactions between agents and ignores long-range interactions (LRIs), which may influence or even determine the collective behavior of MASs. In our paper, a basic framework is developed for analyzing the control costs for reaching consensus of MASs with LRIs and noise perturbation. The theoretical estimate of the control cost from a time and energy perspective will depend on the network diameter, control parameters, noise strength, and network size, and LRIs can promote MASs to reach consensus. We provide some numerical simulations to test our theory. Both theoretical and numerical analyses reveal that there is a trade-off between time and energy costs regardless of whether MASs have LRIs or not, i.e., adjusting control parameters to reduce time cost inevitably leads to an increase in energy cost. Our results provide a new option for controlling MASs: designing control protocols based on LRIs which in some cases have superior performance to typical controllers.

Suggested Citation

  • Yin, Xiangxin & Dai, Haifeng & Zhao, Lingzhi & Zhao, Donghua & Xiao, Rui & Sun, Yongzheng, 2024. "Control costs of long-range interacting multi-agent systems with noise perturbation," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012808
    DOI: 10.1016/j.chaos.2023.114378
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923012808
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.114378?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sharafian, Amin & Sharifi, Alireza & Zhang, Weidong, 2020. "Different types of sliding mode controller for nonlinear fractional multi-Agent system," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    2. Etémé, Armand S. & Tabi, Conrad B. & Mohamadou, Alidou, 2017. "Synchronized nonlinear patterns in electrically coupled Hindmarsh–Rose neural networks with long-range diffusive interactions," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 813-826.
    3. Jing Zheng & Jingyuan Chen & Yakang Jin & Yan Wen & Yijiang Mu & Changjin Wu & Yufeng Wang & Penger Tong & Zhigang Li & Xu Hou & Jinyao Tang, 2023. "Photochromism from wavelength-selective colloidal phase segregation," Nature, Nature, vol. 617(7961), pages 499-506, May.
    4. Chong Chen & Song Liu & Xia-qing Shi & Hugues Chaté & Yilin Wu, 2017. "Weak synchronization and large-scale collective oscillation in dense bacterial suspensions," Nature, Nature, vol. 542(7640), pages 210-214, February.
    5. Rybalova, E.V. & Vadivasova, T.E. & Strelkova, G.I. & Zakharova, A., 2022. "Multiplexing noise induces synchronization in multilayer networks," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    6. Victor Helson & Timo Zwettler & Farokh Mivehvar & Elvia Colella & Kevin Roux & Hideki Konishi & Helmut Ritsch & Jean-Philippe Brantut, 2023. "Density-wave ordering in a unitary Fermi gas with photon-mediated interactions," Nature, Nature, vol. 618(7966), pages 716-720, June.
    7. Lu, Peng & Wen, Feier & Li, Yan & Chen, Dianhan, 2021. "Multi-agent modeling of crowd dynamics under mass shooting cases," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    8. Cui, Kaiyan & Song, Zhanjie & Zhang, Shuo, 2022. "Stability of neutral-type neural network with Lévy noise and mixed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    9. Niklas Boers & Bedartha Goswami & Aljoscha Rheinwalt & Bodo Bookhagen & Brian Hoskins & Jürgen Kurths, 2019. "Complex networks reveal global pattern of extreme-rainfall teleconnections," Nature, Nature, vol. 566(7744), pages 373-377, February.
    10. Gambuzza, Lucia Valentina & Frasca, Mattia & Estrada, Ernesto, 2019. "Second-order consensus protocols based on transformed d-path Laplacians," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 183-194.
    11. Sun, Yongzheng & Zhao, Donghua & Ruan, Jiong, 2010. "Consensus in noisy environments with switching topology and time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4149-4161.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaiwen Li & Ming Wang & Kai Liu, 2021. "The Study on Compound Drought and Heatwave Events in China Using Complex Networks," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    2. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Sharafian, Amin & Kanesan, Jeevan & Khairuddin, Anis Salwa Mohd & Ramanathan, Anand & Sharifi, Alireza & Bai, Xiaoshan, 2023. "A novel approach to state estimation of HIV infection dynamics using fixed-time fractional order observer," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    4. Gao, Shanshan & Zhang, Shenggui & Chen, Xinzhuang, 2023. "Effects of changing the weights of arcs on the consensus convergence rate of a leader–follower multi-agent system," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Mobayen, Saleh & Alattas, Khalid A. & Fekih, Afef & El-Sousy, Fayez F.M. & Bakouri, Mohsen, 2022. "Barrier function-based adaptive nonsingular sliding mode control of disturbed nonlinear systems: A linear matrix inequality approach," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Yifei Yang & Sichen Tao & Haichuan Yang & Zijing Yuan & Zheng Tang, 2023. "Dynamic Complex Network, Exploring Differential Evolution Algorithms from Another Perspective," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    7. Xu, Guiqiong & Meng, Lei, 2023. "A novel algorithm for identifying influential nodes in complex networks based on local propagation probability model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    8. Wu, Zhihai & Peng, Li & Xie, Linbo & Wen, Jiwei, 2013. "Stochastic bounded consensus tracking of leader–follower multi-agent systems with measurement noises based on sampled-data with small sampling delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 918-928.
    9. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    10. Amanda de O. Regueira & Henderson Silva Wanderley, 2022. "Changes in rainfall rates and increased number of extreme rainfall events in Rio de Janeiro city," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3833-3847, December.
    11. Xijin Wang & Fenghua Xie & Zhongshi Zhang & Stefan Liess & Keyan Fang & Chenxi Xu & Feng Shi, 2021. "Complex network of synchronous climate events in East Asian tree-ring data," Climatic Change, Springer, vol. 165(3), pages 1-14, April.
    12. Somnath Mondal & Ashok K. Mishra & Ruby Leung & Benjamin Cook, 2023. "Global droughts connected by linkages between drought hubs," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    13. Zeng, Jie & Xiong, Yong & Liu, Feiyang & Ye, Junqing & Tang, Jinjun, 2022. "Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    14. Alves Xavier, Sílvio Fernando & Xavier, Érika Fialho Morais & Jale, Jader Silva & Stosic, Tatijana & Santos, Carlos Antonio Costa dos, 2021. "Multiscale entropy analysis of monthly rainfall time series in Paraíba, Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    15. Cantisán, Julia & Seoane, Jesús M. & Sanjuán, Miguel A.F., 2023. "Rotating cluster formations emerge in an ensemble of active particles," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    16. Antonio Samuel Alves da Silva & Ikaro Daniel de Carvalho Barreto & Moacyr Cunha-Filho & Rômulo Simões Cezar Menezes & Borko Stosic & Tatijana Stosic, 2022. "Spatial and Temporal Variability of Precipitation Complexity in Northeast Brazil," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    17. Hu, Yuntong & Xiao, Fuyuan, 2022. "An efficient forecasting method for time series based on visibility graph and multi-subgraph similarity," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    18. Parivallal, A. & Sakthivel, R. & Amsaveni, R. & Alzahrani, Faris & Alshomrani, Ali Saleh, 2020. "Observer-based memory consensus for nonlinear multi-agent systems with output quantization and Markov switching topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    19. Budzinski, R.C. & Boaretto, B.R.R. & Prado, T.L. & Lopes, S.R., 2019. "Temperature dependence of phase and spike synchronization of neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 35-42.
    20. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012808. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.