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Volume 7 Issue 5
Sep.  2020

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2020  >  7(5): 1235-1248
Amir Amini, Amir Asif and Arash Mohammadi, "Formation-Containment Control Using Dynamic Event-Triggering Mechanism for Multi-Agent Systems," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1235-1248, Sept. 2020. doi: 10.1109/JAS.2020.1003288
Citation: Amir Amini, Amir Asif and Arash Mohammadi, "Formation-Containment Control Using Dynamic Event-Triggering Mechanism for Multi-Agent Systems," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1235-1248, Sept. 2020. doi: 10.1109/JAS.2020.1003288
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Formation-Containment Control Using Dynamic Event-Triggering Mechanism for Multi-Agent Systems

doi: 10.1109/JAS.2020.1003288
Funds:  This work was partially supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada through the NSERC Discovery (RGPIN-2016-04988)
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    Abstract
  • The paper proposes a novel approach for formation-containment control based on a dynamic event-triggering mechanism for multi-agent systems. The leader-leader and follower-follower communications are reduced by utilizing the distributed dynamic event-triggered framework. We consider two separate sets of design parameters: one set comprising control and dynamic event-triggering parameters for the leaders and a second set similar to the first one with different values for the followers. The proposed algorithm includes two novel stages of co-design optimization to simultaneously compute the two sets of parameters. The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications. Simulations based on non-holonomic mobile robot multi-agent systems quantify the effectiveness of the proposed approach.

     

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    • 1 To improve comprehension, common notation used for leaders and followers is intentionally kept the same in Theorems 2 and 3. For example, $ {\bf{\Xi}} $ in Theorem 2 corresponds to the constraint matrix for the leaders. Likewise, $ {\bf{\Xi}} $ in Theorem 3 corresponds to the constraint matrix for the followers. The difference between them is evident from the context where the symbols are used.
    2 It should be noted that convergence within 1% of the initial disagreement (i.e., $ \delta \thinspace{ = }\thinspace 0.01 $ in (47)) provides a satisfactory level of formation-containment convergence in MAS (37). With $ \delta \thinspace{ = }\thinspace 0.01 $, formation-containment is achieved at $ t^\star \thinspace{ = }\thinspace 9.43 $ in this example. We run simulations using a higher accuracy of $ \delta \thinspace{ = }\thinspace 0.005 $ to better observe the differences between different examples.
    References(45)
  • [1]
    Z. Wang, M. He, T. Zheng, Z. Fan, and G. Liu, “Guaranteed cost consensus for high-dimensional multi-agent systems with timevarying delays,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 181–189, 2017.
    [2]
    W. Ni and D. Cheng, “Leader-following consensus of multi-agent systems under fixed and switching topologies,” Systems Control Lett., vol. 59, no. 3–4, pp. 209–217, 2010. doi: 10.1016/j.sysconle.2010.01.006
    [3]
    A. Shariati and Q. Zhao, “Robust leader-following output regulation of uncertain multi-agent systems with time-varying delay,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 4, pp. 807–817, 2018. doi: 10.1109/JAS.2018.7511141
    [4]
    Z. Li, W. Ren, X. Liu, and M. Fu, “Distributed containment control of multi-agent systems with general linear dynamics in the presence of multiple leaders,” Int. J Robust Nonlin., vol. 23, no. 5, pp. 534–547, 2013. doi: 10.1002/rnc.1847
    [5]
    W. Liu, C. Yang, Y. Sun, and J. Qin, “Observer-based eventtriggered containment control of multi-agent systems with time delay,” Int. J. Systems Science, vol. 48, no. 6, pp. 1217–1225, 2017. doi: 10.1080/00207721.2016.1249036
    [6]
    T.-H. Cheng, Z. Kan, J. R. Klotz, J. M. Shea, and W. E. Dixon, “Decentralized event-triggered control of networked systems part 2: Containment control, ” in Proc. IEEE American Control Conf., 2015, pp. 5444–5448.
    [7]
    L. Ma, H. Min, S. Wang, Y. Liu, and Z. Liu, “Distributed containment control of networked nonlinear second-order systems with unknown parameters,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 232–239, 2016.
    [8]
    A. Mondal, L. Behera, S. R. Sahoo, and A. Shukla, “A novel multi-agent formation control law with collision avoidance,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 558–568, 2017. doi: 10.1109/JAS.2017.7510565
    [9]
    X. Ge and Q.-L. Han, “Distributed formation control of networked multi-agent systems using a dynamic event-triggered communication mechanism,” IEEE Trans. Ind. Electron., vol. 64, no. 10, pp. 8118–8127, 2017. doi: 10.1109/TIE.2017.2701778
    [10]
    L. Han, X. Dong, Q. Li, and Z. Ren, “Formation-containment control for second-order multi-agent systems with time-varying delays,” Neurocomputing, vol. 218, pp. 439–447, 2016. doi: 10.1016/j.neucom.2016.09.001
    [11]
    X. Dong, Y. Hua, Y. Zhou, Z. Ren, and Y. Zhong, “Theory and experiment on formation-containment control of multiple multirotor unmanned aerial vehicle systems,” IEEE Trans. Automation Science and Engineering, vol. 16, no. 1, pp. 229–240, 2018.
    [12]
    Y. Hua, X. Dong, L. Han, Q. Li, and Z. Ren, “Formationcontainment tracking for general linear multi-agent systems with a tracking-leader of unknown control input,” Systems &Control Letters, vol. 122, pp. 67–76, 2018.
    [13]
    Y.-W. Wang, X.-K. Liu, J.-W. Xiao, and Y. Shen, “Output formation-containment of interacted heterogeneous linear systems by distributed hybrid active control,” Automatica, vol. 93, pp. 26–32, 2018. doi: 10.1016/j.automatica.2018.03.020
    [14]
    X. Dong, Q. Li, Z. Ren, and Y. Zhong, “Output formationcontainment analysis and design for general linear timeinvariant multi-agent systems,” J. Franklin I., vol. 353, no. 2, pp. 322–344, 2016. doi: 10.1016/j.jfranklin.2015.11.004
    [15]
    W. Jiang, G. Wen, Z. Peng, T. Huang, and R. A. Rahmani, “Fully distributed formation-containment control of heterogeneous linear multi-agent systems,” IEEE Trans. Automatic Control, vol. 64, no. 9, pp. 3889–3896, 2019.
    [16]
    S. Zuo, Y. Song, F. L. Lewis, and A. Davoudi, “Time-varying output formation containment of general linear homogeneous and heterogeneous multiagent systems,” IEEE Trans. Control of Network Systems, vol. 6, no. 2, pp. 537–548, 2018.
    [17]
    D. Li, W. Zhang, W. He, C. Li, and S. S. Ge, “Two-layer distributed formation-containment control of multiple euler-lagrange systems by output feedback,” IEEE Trans. Cybernetics, vol. 49, no. 2, pp. 675–687, 2018.
    [18]
    C. Li, L. Chen, Y. Guo, and G. Ma, “Formation-containment control for networked euler-lagrange systems with input saturation,” Nonlinear Dynamics, vol. 91, no. 2, pp. 1307–1320, 2018. doi: 10.1007/s11071-017-3946-7
    [19]
    Y. Wang, Y. Song, and W. Ren, “Distributed adaptive finitetime approach for formation-containment control of networked nonlinear systems under directed topology,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 7, pp. 3164–3175, 2017.
    [20]
    L. Chen, C. Li, B. Xiao, and Y. Guo, “Formation-containment control of networked euler-lagrange systems: An event-triggered framework,” ISA Transactions, vol. 86, pp. 87–97, 2019. doi: 10.1016/j.isatra.2018.10.019
    [21]
    L. Galbusera, G. Ferrari-Trecate, and R. Scattolini, “A hybrid model predictive control scheme for containment and distributed sensing in multi-agent systems,” Syst. Control Lett., vol. 62, no. 5, pp. 413–419, 2013. doi: 10.1016/j.sysconle.2013.02.007
    [22]
    M. Yu, C. Yan, D. Xie, and G. Xie, “Event-triggered tracking consensus with packet losses and time-varying delays,” IEEE/CAA J. Autom. Sinica, vol. 3, no. 2, pp. 165–173, 2016. doi: 10.1109/JAS.2016.7451104
    [23]
    H. Xia, W. X. Zheng, and J. Shao, “Event-triggered containment control for second-order multi-agent systems with sampled position data,” ISA Transactions, 2017.
    [24]
    G. Miao, J. Cao, A. Alsaedi, and F. E. Alsaadi, “Event-triggered containment control for multi-agent systems with constant time delays,” J. Franklin I., vol. 354, no. 15, pp. 6956–6977, 2017. doi: 10.1016/j.jfranklin.2017.08.010
    [25]
    W. Zou and Z. Xiang, “Event-triggered containment control of second-order nonlinear multi-agent systems,” J. Franklin Institute, vol. 356, no. 17, pp. 10421–10438, 2019. doi: 10.1016/j.jfranklin.2018.05.060
    [26]
    W. Zou and Z. Xiang, “Event-triggered distributed containment control of heterogeneous linear multi-agent systems by an output regulation approach, ” Int. J. Systems Science, vol. 48, no. 10, pp. 2041–2054, 2017.
    [27]
    C. Peng and T. C. Yang, “Event-triggered communication and H∞ control co-design for networked control systems,” Automatica, vol. 49, no. 5, pp. 1326–1332, 2013. doi: 10.1016/j.automatica.2013.01.038
    [28]
    M. Abdelrahim, R. Postoyan, J. Daafouz, and D. Nešić, “Codesign of output feedback laws and event-triggering conditions for linear systems, ” in Proc. 53rd IEEE CDC, 2014, pp. 3560–3565.
    [29]
    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, 2020.
    [30]
    X. Yi, K. Liu, D. V. Dimarogonas, and K. H. Johansson, “Dynamic event-triggered and self-triggered control for multi-agent systems,” IEEE Trans. Autom. Control, vol. 64, no. 8, pp. 3300–3307, 2019.
    [31]
    W. He, B. Xu, Q.-L. Han, and F. Qian, “Adaptive consensus control of linear multiagent systems with dynamic eventtriggered strategies,” IEEE Trans. Cybern., 2019.
    [32]
    T.-H. Cheng, Z. Kan, J. R. Klotz, J. M. Shea, and W. E. Dixon, “Event-triggered control of multiagent systems for fixed and time-varying network topologies,” IEEE Trans. Autom. Control, vol. 62, no. 10, pp. 5365–5371, 2017. doi: 10.1109/TAC.2017.2693824
    [33]
    L. Ding, Q.-L. Han, X. Ge, and X.-M. Zhang, “An overview of recent advances in event-triggered consensus of multiagent systems,” IEEE Trans. Cybern., vol. 48, no. 4, pp. 1110–1123, 2018. doi: 10.1109/TCYB.2017.2771560
    [34]
    D. Yang, W. Ren, X. Liu, and W. Chen, “Decentralized eventtriggered consensus for linear multi-agent systems under general directed graphs,” Automatica, vol. 69, pp. 242–249, 2016. doi: 10.1016/j.automatica.2016.03.003
    [35]
    G. S. Seyboth, D. V. Dimarogonas, and K. H. Johansson, “Event-based broadcasting for multi-agent average consensus,” Automatica, vol. 49, no. 1, pp. 245–252, 2013. doi: 10.1016/j.automatica.2012.08.042
    [36]
    L. Xing, C. Wen, F. Guo, Z. Liu, and H. Su, “Event-based consensus for linear multiagent systems without continuous communication,” IEEE Trans. Cybern., vol. 47, no. 8, pp. 2132–2142, 2016.
    [37]
    J. Almeida, C. Silvestre, and A. Pascoal, “Synchronization of multiagent systems using event-triggered and self-triggered broadcasts,” IEEE Trans. Autom. Control, vol. 62, no. 9, pp. 4741–4746, 2017. doi: 10.1109/TAC.2017.2671029
    [38]
    X. Liu, C. Du, P. Lu, and D. Yang, “Distributed event-triggered feedback consensus control with state-dependent threshold for general linear multi-agent systems,” Int. J Robust Nonlin., vol. 27, no. 15, pp. 2589–2609, 2017. doi: 10.1002/rnc.3700
    [39]
    X. Dong, Q. Li, Q. Zhao, and Z. Ren, “Time-varying group formation analysis and design for general linear multi-agent systems with directed topologies,” Int. J. Robust and Nonlinear Control, vol. 27, no. 9, pp. 1640–1652, 2017.
    [40]
    A. Gusrialdi and Z. Qu, “Distributed estimation of all the eigenvalues and eigenvectors of matrices associated with strongly connected digraphs,” IEEE Contr. Syst. Lett., vol. 1, no. 2, pp. 328–333, 2017. doi: 10.1109/LCSYS.2017.2717799
    [41]
    I. Shames, T. Charalambous, C. N. Hadjicostis, and M. Johansson, “Distributed network size estimation and average degree estimation and control in networks isomorphic to directed graphs, ” in Proc. IEEE Communication, Control, and Computing (Allerton), 2012, pp. 1885–1892.
    [42]
    J. R. 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, 2003. doi: 10.1109/TRA.2003.819598
    [43]
    S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory. SIAM, 1994.
    [44]
    G. Chiandussi, M. Codegone, S. Ferrero, and F. E. Varesio, “Comparison of multi-objective optimization methodologies for engineering applications,” Computers &Mathematics With Applications, vol. 63, no. 5, pp. 912–942, 2012.
    [45]
    M. Abdelrahim, R. Postoyan, J. Daafouz, D. Nešić, and M. Heemels, “Co-design of output feedback laws and eventtriggering conditions for the L2-stabilization of linear systems,” Automatica, vol. 87, pp. 337–344, 2018. doi: 10.1016/j.automatica.2017.10.008
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    Highlights

    • The paper proposes a novel approach for formation-containment control based on a dynamic event-triggering mechanism for general linear multi-agent systems. The leader-leader and follower-follower communications are reduced by utilizing a distributed dynamic event-triggered framework.
    • Two separate sets of design parameters are considered: (i) The first set comprises of the control and dynamic event-triggering parameters for the leaders, and; (ii) The second set is similar to the first one with different values for the followers. The proposed algorithm includes two novel stages of co-design optimization to simultaneously compute the two sets of parameters.
    • The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications.

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