A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 10 Issue 10
Oct.  2023

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
J. Y. Chai, Q. Lu, X. D. Tao, D. L. Peng, and  B. T. Zhang,  “Dynamic event-triggered fixed-time consensus control and its applications to magnetic map construction,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 10, pp. 2000–2013, Oct. 2023. doi: 10.1109/JAS.2023.123444
Citation: J. Y. Chai, Q. Lu, X. D. Tao, D. L. Peng, and  B. T. Zhang,  “Dynamic event-triggered fixed-time consensus control and its applications to magnetic map construction,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 10, pp. 2000–2013, Oct. 2023. doi: 10.1109/JAS.2023.123444

Dynamic Event-Triggered Fixed-Time Consensus Control and Its Applications to Magnetic Map Construction

doi: 10.1109/JAS.2023.123444
Funds:  This work was supported in part by the National Natural Science Foundation of China (62073108), the Zhejiang Provincial Natural Science Foundation (LZ23F030004), the Key Research and Development Project of Zhejiang Province (2019C04018), and the Fundamental Research Funds for the Provincial Universities of Zhejiang (GK229909299001-004)
More Information
  • This article deals with the consensus problem of multi-agent systems by developing a fixed-time consensus control approach with a dynamic event-triggered rule. First, a new fixed-time stability condition is obtained where the less conservative settling time is given such that the theoretical settling time can well reflect the real consensus time. Second, a dynamic event-triggered rule is designed to decrease the use of chip and network resources where Zeno behaviors can be avoided after consensus is achieved, especially for finite/fixed-time consensus control approaches. Third, in terms of the developed dynamic event-triggered rule, a fixed-time consensus control approach by introducing a new item is proposed to coordinate the multi-agent system to reach consensus. The corresponding stability of the multi-agent system with the proposed control approach and dynamic event-triggered rule is analyzed based on Lyapunov theory and the fixed-time stability theorem. At last, the effectiveness of the dynamic event-triggered fixed-time consensus control approach is verified by simulations and experiments for the problem of magnetic map construction based on multiple mobile robots.

     

  • loading
  • [1]
    F. Amigoni, V. Caglioti, and G. Fontana, “A perceptive multirobot system for monitoring electro-magnetic fields,” in Proc. IEEE Symp. Virtual Environments, Human-Computer Interfaces and Measurement Systems, Boston, USA, 2004, pp. 95–100.
    [2]
    Y. Cao, W. Yu, W. Ren, and G. Chen, “An overview of recent progress in the study of distributed multi-agent coordination,” IEEE Trans. Ind. Inf., vol. 9, no. 1, pp. 427–438, Feb. 2013. doi: 10.1109/TII.2012.2219061
    [3]
    L. Hou, F. Fan, J. Fu, and J. Wang, “Time-varying algorithm for swarm robotics,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 217–222, Jan. 2018. doi: 10.1109/JAS.2017.7510685
    [4]
    Q. Lu, Q.-L. Han, D. Peng, and Y. Choi, “Decision and event-based fixed-time consensus control for electromagnetic source localization,” IEEE Trans. Cybern., vol. 52, no. 4, pp. 2186–2199, Apr. 2022. doi: 10.1109/TCYB.2020.3005964
    [5]
    J. Qin, Q. Ma, Y. Shi, and L. Wang, “Recent advances in consensus of multi-agent systems: A brief survey,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 4972–4983, Jun. 2017. doi: 10.1109/TIE.2016.2636810
    [6]
    J. Wang, Y. Hong, J. Wang, J. Xu, Y. Tang, Q.-L. Han, and J. Kurths, “Cooperative and competitive multi-agent systems: From optimization to games,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 763–783, May 2022. doi: 10.1109/JAS.2022.105506
    [7]
    A. Hirata, Y. Diao, T. Onishi, K. Sasaki, S. Ahn, D. Colombi, V. De Santis, I. Laakso, L. Giaccone, W. Joseph, E. A. Rashed, W. Kainz, and J. Chen, “Assessment of human exposure to electromagnetic fields: Review and future directions,” IEEE Trans. Electromagn. Compat., vol. 63, no. 5, pp. 1619–1630, Oct. 2021. doi: 10.1109/TEMC.2021.3109249
    [8]
    B. Li, T. Gallagher, A. G. Dempster, and C. Rizos, “How feasible is the use of magnetic field alone for indoor positioning?” in Proc. Int. Conf. Indoor Positioning and Indoor Navigation, Sydney, Australia, 2012, pp. 1–9.
    [9]
    S. M. Potirakis, A. Schekotov, T. Asano, and M. Hayakawa, “Natural time analysis on the ultra-low frequency magnetic field variations prior to the 2016 Kumamoto (Japan) earthquakes,” J. Asian Earth Sci., vol. 154, pp. 419–427, Apr. 2018. doi: 10.1016/j.jseaes.2017.12.036
    [10]
    B. Wang, D. Xia, Y. Yu, J. Jia, Y. Nie, and X. Wang, “Detecting the sensitivity of magnetic response on different pollution sources — A case study from typical mining cities in northwestern China,” Environ. Pollut., vol. 207, pp. 288–298, Dec. 2015. doi: 10.1016/j.envpol.2015.08.041
    [11]
    H. Liu, G. Zhou, T. Lei, and F. Tian, “Finite-time stability of linear time-varying continuous system with time-delay,” in Proc. 27th Chinese Control and Decision Conf., Qingdao, China, 2015, pp. 6063–6068.
    [12]
    R. R. Nair, L. Behera, and S. Kumar, “Event-triggered finite-time integral sliding mode controller for consensus-based formation of multirobot systems with disturbances,” IEEE Trans. Contr. Syst. Technol., vol. 27, no. 1, pp. 39–47, Jan. 2019. doi: 10.1109/TCST.2017.2757448
    [13]
    Y. Liu, F. Zhang, P. Huang, and Y. Lu, “Fixed-time consensus tracking for second-order multiagent systems under disturbance,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 51, no. 8, pp. 4883–4894, Aug. 2021. doi: 10.1109/TSMC.2019.2944392
    [14]
    B. Ning, Q.-L. Han, Z. Zuo, L. Ding, Q. Lu, and X. Ge, “Fixed-time and prescribed-time consensus control of multiagent systems and its applications: A survey of recent trends and methodologies,” IEEE Trans. Ind. Inf., vol. 19, no. 2, pp. 1121–1135, Feb. 2023. doi: 10.1109/TII.2022.3201589
    [15]
    Q. Xiao, H. Liu, and Y. Wang, “An improved finite-time and fixed-time stable synchronization of coupled discontinuous neural networks,” IEEE Trans. Neural Netw. Learn. Syst., vol. 34, no. 7, pp. 3516–3526, Jul. 2023. doi: 10.1109/TNNLS.2021.3116320
    [16]
    A. Polyakov, “Nonlinear feedback design for fixed-time stabilization of linear control systems,” IEEE Trans. Autom. Control, vol. 57, no. 8, pp. 2106–2110, Aug. 2012. doi: 10.1109/TAC.2011.2179869
    [17]
    I. Ahmad, X. Ge, and Q.-L. Han, “Decentralized dynamic event-triggered communication and active suspension control of in-wheel motor driven electric vehicles with dynamic damping,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 5, pp. 971–986, May 2021. doi: 10.1109/JAS.2021.1003967
    [18]
    D. Liu and G.-H. Yang, “A dynamic event-triggered control approach to leader-following consensus for linear multiagent systems,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 51, no. 10, pp. 6271–6279, 2021. doi: 10.1109/TSMC.2019.2960062
    [19]
    J. Liu, Y. Yu, J. Sun, and C. Sun, “Distributed event-triggered fixed-time consensus for leader-follower multiagent systems with nonlinear dynamics and uncertain disturbances,” Int. J. Robust Nonlinear Control, vol. 28, no. 11, pp. 3543–3559, Jul. 2018. doi: 10.1002/rnc.4098
    [20]
    J. Liu, Y. Zhang, Y. Yu, and C. Sun, “Fixed-time leader-follower consensus of networked nonlinear systems via event/self-triggered control,” IEEE Trans. Neural Netw. Learn. Syst., vol. 31, no. 11, pp. 5029–5037, Nov. 2020. doi: 10.1109/TNNLS.2019.2957069
    [21]
    I. Ahmed, M. Rehan, and N. Iqbal, “A novel exponential approach for dynamic event-triggered leaderless consensus of nonlinear multi-agent systems over directed graphs,” IEEE Trans. Circuits Syst. II: Express Briefs, vol. 69, no. 3, pp. 1782–1786, Mar. 2022.
    [22]
    X. Ge, S. Xiao, Q.-L. Han, X.-M. Zhang, and D. Ding, “Dynamic event-triggered scheduling and platooning control co-design for automated vehicles over vehicular ad-hoc networks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 31–46, Jan. 2022. doi: 10.1109/JAS.2021.1004060
    [23]
    X. Ge, Q.-L. Han, L. Ding, Y.-L. Wang, and X.-M. Zhang, “Dynamic event-triggered distributed coordination control and its applications: A survey of trends and techniques,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 50, no. 9, pp. 3112–3125, Sept. 2020. doi: 10.1109/TSMC.2020.3010825
    [24]
    G. Zhao and C. Hua, “A hybrid dynamic event-triggered approach to consensus of multiagent systems with external disturbances,” IEEE Trans. Autom. Control, vol. 66, no. 7, pp. 3213–3220, Jul. 2021. doi: 10.1109/TAC.2020.3018437
    [25]
    L. Zhao, H. Wu, and J. Cao, “Finite/fixed-time bipartite consensus for networks of diffusion PDEs via event-triggered control,” Inf. Sci., vol. 609, pp. 1435–1450, Sept. 2022. doi: 10.1016/j.ins.2022.07.151
    [26]
    J. Liu, G. Ran, Y. Wu, L. Xue, and C. Sun, “Dynamic event-triggered practical fixed-time consensus for nonlinear multiagent systems,” IEEE Trans. Circuits Syst. II: Express Briefs, vol. 69, no. 4, pp. 2156–2160, Apr. 2022.
    [27]
    L. Feng, J. Yu, C. Hu, C. Yang, and H. Jiang, “Nonseparation method-based finite/fixed-time synchronization of fully complex-valued discontinuous neural networks,” IEEE Trans. Cybern., vol. 51, no. 6, pp. 3212–3223, Jun. 2021. doi: 10.1109/TCYB.2020.2980684
    [28]
    G. Ji, C. Hu, J. Yu, and H. Jiang, “Finite-time and fixed-time synchronization of discontinuous complex networks: A unified control framework design,” J. Franklin Inst., vol. 355, no. 11, pp. 4665–4685, Jul. 2018. doi: 10.1016/j.jfranklin.2018.04.026
    [29]
    C. Hu and H. Jiang, “Special functions-based fixed-time estimation and stabilization for dynamic systems,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 52, no. 5, pp. 3251–3262, May 2022. doi: 10.1109/TSMC.2021.3062206
    [30]
    C.-Y. Kim, D. Song, Y. Xu, J. Yi, and X. Wu, “Cooperative search of multiple unknown transient radio sources using multiple paired mobile robots,” IEEE Trans. Robot., vol. 30, no. 5, pp. 1161–1173, Oct. 2014. doi: 10.1109/TRO.2014.2333097
    [31]
    J. Nam, W. Lee, B. Jang, and G. Jang, “Magnetic navigation system utilizing resonant effect to enhance magnetic field applied to magnetic robots,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 4701–4709, Jun. 2017. doi: 10.1109/TIE.2017.2669886
    [32]
    J. R. T. Lawton, R. W. Beard, and B. J. Young, “A decentralized approach to formation maneuvers,” IEEE Trans. Robot. Autom., vol. 19, no. 6, pp. 933–941, Dec. 2003. doi: 10.1109/TRA.2003.819598
    [33]
    R. Wei and R. W. Beard, Distributed Consensus in Multi-Vehicle Cooperative Control. London, UK: Springer, 2008.
    [34]
    W. Hu, C. Yang, T. Huang, and W. Gui, “A distributed dynamic event-triggered control approach to consensus of linear multiagent systems with directed networks,” IEEE Trans. Cybern., vol. 50, no. 2, pp. 869–874, Feb. 2020. doi: 10.1109/TCYB.2018.2868778
    [35]
    Q. Lu, Q.-L. Han, C. Zhong, B. Zhang, J. Wang, S. Liu, and J. Wang, “Finite-time consensus analysis under directed communication topologies for multi-agent systems,” in Proc. 20th World Congr. Int. Federation of Autom. Control, Toulouse, France, 2017, pp. 621–626.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(6)

    Article Metrics

    Article views (268) PDF downloads(87) Cited by()

    Highlights

    • A new fixed-time stability condition is obtained where the less conservative settling time is given such that the theoretical settling time can well reflect the real consensus time
    • A dynamic event-triggered rule is designed to reduce the use of chip and communication resources by introducing an internal variable where Zeno behaviors can be avoided after consensus is achieved for finite/fixed-time consensus control approaches
    • In terms of the developed dynamic event-triggered rule, a fixed-time consensus control approach by introducing a new item such that the proposed controller can enable the second-order nonlinear multi-agent system to reach consensus quickly
    • The dynamic event-triggered fixed-time control approach is used to guide the robots to construct the magnetic map

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return