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Volume 11 Issue 6
Jun.  2024

IEEE/CAA Journal of Automatica Sinica

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Z. Zuo, J. Tang, R. Ke, and  Q.-L. Han,  “Hyperbolic tangent function-based protocols for global/semi-global finite-time consensus of multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 6, pp. 1381–1397, Jun. 2024. doi: 10.1109/JAS.2024.124485
Citation: Z. Zuo, J. Tang, R. Ke, and  Q.-L. Han,  “Hyperbolic tangent function-based protocols for global/semi-global finite-time consensus of multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 6, pp. 1381–1397, Jun. 2024. doi: 10.1109/JAS.2024.124485

Hyperbolic Tangent Function-Based Protocols for Global/Semi-Global Finite-Time Consensus of Multi-Agent Systems

doi: 10.1109/JAS.2024.124485
Funds:  This work was supported by the National Natural Science Foundation of China (62073019)
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  • This paper investigates the problem of global/semi-global finite-time consensus for integrator-type multi-agent systems. New hyperbolic tangent function-based protocols are proposed to achieve global and semi-global finite-time consensus for both single-integrator and double-integrator multi-agent systems with leaderless undirected and leader-following directed communication topologies. These new protocols not only provide an explicit upper-bound estimate for the settling time, but also have a user-prescribed bounded control level. In addition, compared to some existing results based on the saturation function, the proposed approach considerably simplifies the protocol design and the stability analysis. Illustrative examples and an application demonstrate the effectiveness of the proposed protocols.

     

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  • [1]
    J. Lin, A. S. Morse, and B. D. O. Anderson, “The multi-agent rendezvous problem,” in Proc. 42nd IEEE Int. Conf. Decision and Control, vol. 2, pp. pp. 1508–1513, Maui, Hawaii, USA, Dec. 9–12, 2003.
    [2]
    Y. Dong and J. Huang, “A leader-following rendezvous problem of double integrator multi-agent systems,” Automatica, vol. 49, no. 5, pp. 1386–1391, May 2013. doi: 10.1016/j.automatica.2013.02.024
    [3]
    W. He, G. Chen, Q.-L Han, W. Du, J. Cao, and F. Qian, “Multiagent systems on multilayer networks: Synchronization analysis and network design,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 47, no. 7, pp. 1655–1667, Jul. 2017. doi: 10.1109/TSMC.2017.2659759
    [4]
    R. Olfati-Saber, “Flocking for multi-agent dynamic systems: Algorithms and theory,” IEEE Trans. Automatic Control, vol. 51, no. 3, pp. 401–420, Mar. 2006. doi: 10.1109/TAC.2005.864190
    [5]
    B. Ning, Q.-L. Han, Z. Zuo, and J. Zhang, “Collective behaviors of mobile robots beyond the nearest neighbor rules with switching topology,” IEEE Trans. Cybernetics, vol. 48, no. 5, pp. 1577–1590, May 2018. doi: 10.1109/TCYB.2017.2708321
    [6]
    J. Fax and R. Murray, “Information flow and cooperative control of vehicle formations,” IEEE Trans. Automatic Control, vol. 49, no. 9, pp. 1465–1476, Sep. 2004. doi: 10.1109/TAC.2004.834433
    [7]
    H. Du, W. Zhu, G. Wen, Z. Duan, and J. Lu, “Distributed formation control of multiple quadrotor aircraft based on nonsmooth consensus algorithms,” IEEE Trans. Cybernetics, vol. 49, no. 1, pp. 342–353, Jan. 2019. doi: 10.1109/TCYB.2017.2777463
    [8]
    Z. Peng, J. Wang, D. Wang, and Q.-L. Han, “An overview of recent advances in coordinated control of multiple autonomous surface vehicles,” IEEE Trans. Industrial Informatics, vol. 17, no. 2, pp. 732–745, Feb. 2021. doi: 10.1109/TII.2020.3004343
    [9]
    L. Wang, D. Zhu, W. Pang, and C. Luo, “A novel obstacle avoidance consensus control for multi-AUV formation system,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1304–1318, May 2023. doi: 10.1109/JAS.2023.123201
    [10]
    Y. Liu and L. Li, “Adaptive leader-follower consensus control of multiple flexible manipulators with actuator failures and parameter uncertainties,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 1020–1031, Apr. 2023. doi: 10.1109/JAS.2023.123093
    [11]
    M. Cecchi, M. Paiano, A. Mannucci, A. Palleschi, F. Pecora, and L. Pallottino, “Priority-based distributed coordination for heterogeneous multi-robot systems with realistic assumptions,” IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 6131–6138, Jul. 2021. doi: 10.1109/LRA.2021.3091016
    [12]
    H. Zhang, J. Sun, and Z. Wang, “Distributed control of nonholonomic robots without global position measurements subject to unknown slippage constraints,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 2, pp. 354–364, Feb. 2022. doi: 10.1109/JAS.2021.1004329
    [13]
    B. Ning, Q.-L. Han, and Z. Zuo, “Distributed optimization of multiagent systems with preserved network connectivity,” IEEE Trans. Cybnertics, vol. 49, no. 11, pp. 3980–3990, Nov. 2019.
    [14]
    D. Li and B. De Schutter, “Distributed model-free adaptive predictive control for urban traffic networks,” IEEE Trans. Control Systems Technology, vol. 30, no. 1, pp. 180–192, Jan. 2022. doi: 10.1109/TCST.2021.3059460
    [15]
    Z. Zuo and L. Tie, “A new class of finite-time nonlinear consensus protocols for multi-agent systems,” Int. Journal of Control, vol. 87, no. 2, pp. 363–370, Feb. 2014. doi: 10.1080/00207179.2013.834484
    [16]
    S. P. Bhat and D. S. Bernstein, “Finite-time stability of continuous autonomous systems,” SIAM Journal on Control and Optimization, vol. 38, no. 3, pp. 751–766, Jan. 2000. doi: 10.1137/S0363012997321358
    [17]
    F. Xiao, L. Wang, J. Chen, and Y. Gao, “Finite-time formation control for multi-agent systems,” Automatica, vol. 45, no. 11, pp. 2605–2611, Nov. 2009. doi: 10.1016/j.automatica.2009.07.012
    [18]
    L. Wang and F. Xiao, “Finite-time consensus problems for networks of dynamic agents,” IEEE Trans. Automatic Control, vol. 55, no. 4, pp. 950–955, Apr 2010. doi: 10.1109/TAC.2010.2041610
    [19]
    S. Li, H. Du, and X. Lin, “Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics,” Automatica, vol. 47, no. 8, pp. 1706–1712, Aug. 2011. doi: 10.1016/j.automatica.2011.02.045
    [20]
    Y. Zhao, Z. Duan, G. Wen, and G. Chen, “Distributed finite-time tracking for a multi-agent system under a leader with bounded unknown acceleration,” Systems & Control Letters, vol. 81, pp. 8–13, Jul 2015.
    [21]
    Y. Liu and Z. Geng, “Finite-time formation control for linear multi-agent systems: A motion planning approach,” Systems & Control Letters, vol. 85, pp. 54–60, Nov. 2015.
    [22]
    F. Wang, X. Chen, Y. He, and M. Wu, “Finite-time consensus problem for second-order multi-agent systems under switching topologies: Finite-time consensus under switching topologies,” Asian Journal of Control, vol. 19, no. 5, pp. 1756–1766, 2017. doi: 10.1002/asjc.1486
    [23]
    G. Dong, H. Li, H. Ma, and R. Lu, “Finite-time consensus tracking neural network FTC of multi-agent systems,” IEEE Trans. Neural Networks and Learning Systems, vol. 32, no. 2, pp. 653–662, Feb. 2021. doi: 10.1109/TNNLS.2020.2978898
    [24]
    A. Sharghi, M. Baradarannia, and F. Hashemzadeh, “Finite-time-estimation-based surrounding control for a class of unknown nonlinear multi-agent systems,” Nonlinear Dynamics, vol. 96, pp. 1795–1804, Mar. 2019. doi: 10.1007/s11071-019-04884-z
    [25]
    J. Wang, Y. Yan, Z. Liu, C. P. Chen, C. Zhang, and K. Chen, “Finite-time consensus control for multi-agent systems with full-state constraints and actuator failures,” Neural Networks, vol. 157, pp. 350–363, Jan. 2023. doi: 10.1016/j.neunet.2022.10.028
    [26]
    Y. Li, Y.-X. Li, and S. Tong, “Event-based finite-time control for nonlinear multi-agent systems with asymptotic tracking,” IEEE Trans. Automatic Control, vol. 68, no. 6, pp. 3790–3797, Jun. 2023. doi: 10.1109/TAC.2022.3197562
    [27]
    T. Han, Z.-H. Guan, R.-Q. Liao, J. Chen, M. Chi, and D.-X. He, “Distributed finite-time formation tracking control of multi-agent systems via FTSMC approach,” IET Control Theory & Applications, vol. 11, no. 15, pp. 2585–2590, Oct. 2017.
    [28]
    J. Cortés, “Finite-time convergent gradient flows with applications to network consensus,” Automatica, vol. 42, no. 11, pp. 1993–2000, Nov. 2006. doi: 10.1016/j.automatica.2006.06.015
    [29]
    X. Shi, X. Xu, J. Cao, and X. Yu, “Finite-time convergent primal-dual gradient dynamics with applications to distributed optimization,” IEEE Trans. Cybernetics, vol. 53, no. 5, pp. 3240–3252, May 2023. doi: 10.1109/TCYB.2022.3179519
    [30]
    S. Li and X. Wang, “Finite-time consensus and collision avoidance control algorithms for multiple AUVs,” Automatica, vol. 49, no. 11, pp. 3359–3367, Nov. 2013. doi: 10.1016/j.automatica.2013.08.003
    [31]
    M. Ye, Q.-L. Han, L. Ding, and S. Xu, “Fully distributed nash equilibrium seeking for high-order players with actuator limitations,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 6, pp. 1434–1444, Jun. 2023. doi: 10.1109/JAS.2022.105983
    [32]
    J. Zhao, H. Shen, B. Li, and J. Wang, “Finite-time H control for a class of Markovian jump delayed systems with input saturation,” Nonlinear Dynamics, vol. 73, pp. 1–2, Jul. 1099.
    [33]
    Q. Hu, B. Li, and J. Qi, “Disturbance observer based finite-time attitude control for rigid spacecraft under input saturation,” Aerospace Science and Technology, vol. 39, pp. 13–21, Dec. 2014. doi: 10.1016/j.ast.2014.08.009
    [34]
    D.-H. Zhai and Y. Xia, “Finite-time control of teleoperation systems with input saturation and varying time delays,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 47, no. 7, pp. 1522–1534, Jul. 2017. doi: 10.1109/TSMC.2016.2631601
    [35]
    Z. Ma and P. Huang, “Adaptive Neural-network controller for an uncertain rigid manipulator with input saturation and full-order state constraint,” IEEE Trans. Cybernetics, vol. 52, no. 5, pp. 2907–2915, May 2022. doi: 10.1109/TCYB.2020.3022084
    [36]
    G. Miao and Q. Ma, “Group consensus of the first-order multi-agent systems with nonlinear input constraints,” Neurocomputing, vol. 161, pp. 113–119, Aug. 2015. doi: 10.1016/j.neucom.2015.02.058
    [37]
    J. Fu, G. Wen, W. Yu, and Z. Ding, “Finite-time consensus for second-order multi-agent systems with input saturation,” IEEE Trans. Circuits and Systems II: Express Briefs, vol. 65, no. 11, pp. 1758–1762, Nov. 2018.
    [38]
    D. Chen, T. Lu, X. Liu, and W. Yu, “Finite-time consensus of multiagent systems with input saturation and disturbance,” Int. Journal of Robust and Nonlinear Control, vol. 31, no. 6, pp. 2097–2109, Apr. 2021. doi: 10.1002/rnc.5029
    [39]
    M. Cai and Z. Xiang, “Adaptive finite-time consensus tracking for multiple uncertain mechanical systems with input saturation: Finite-time consensus tracking for multiple mechanical systems,” Int. Journal of Robust and Nonlinear Control, vol. 27, no. 9, pp. 1653–1676, 2017. doi: 10.1002/rnc.3741
    [40]
    Z. Zhang, Z. Zuo, and Y. Wang, “Finite-time consensus of neutrally stable multi-agent systems in the presence of input saturation,” Journal of the Franklin Institute, vol. 356, no. 2, pp. 894–907, Jan. 2019. doi: 10.1016/j.jfranklin.2017.12.013
    [41]
    B. Zhang, Y. Jia, and F. Matsuno, “Finite-time observers for multi-agent systems without velocity measurements and with input saturations,” Systems & Control Letters, vol. 68, pp. 86–94, Jun. 2014.
    [42]
    Y. Cheng, H. Du, Y. He, and R. Jia, “Distributed finite-time attitude regulation for multiple rigid spacecraft via bounded control,” Information Sciences, vol. 328, pp. 144–157, Jan. 2016. doi: 10.1016/j.ins.2015.08.042
    [43]
    X. Shi, G. Wen, J. Cao, and X. Yu, “Finite-time distributed average tracking for multi-agent optimization with bounded inputs,” IEEE Trans. Automatic Control, vol. 68, no. 8, pp. 4948–4955, Aug. 2023. doi: 10.1109/TAC.2022.3209406
    [44]
    Z. Zuo, X. Li, B. Ning, and Q.-L. Han, “Global finite-time stabilization of first-order systems with bounded controls,” IEEE Trans. Circuits and Systems II: Express Briefs, vol. 70, no. 7, pp. 2440–2444, Jul. 2023.
    [45]
    Y. Orlov, “Finite time stability and robust control synthesis of uncertain switched systems,” SIAM Journal on Control and Optimization, vol. 43, no. 4, pp. 1253–1271, Jan. 2004. doi: 10.1137/S0363012903425593
    [46]
    Z. Deng, Y. Xu, H. Sun, and X. Shen, “Distributed, bounded and finite-time convergence secondary frequency control in an autonomous microgrid,” IEEE Trans. Smart Grid, vol. 10, no. 3, pp. 2776–2788, May 2019. doi: 10.1109/TSG.2018.2810287
    [47]
    Z. Zuo, Q.-L. Han, B. Ning, X. Ge, and X.-M. Zhang, “An overview of recent advances in fixed-time cooperative control of multiagent systems,” IEEE Trans. Industrial Informatics, vol. 14, no. 6, pp. 2322–2334, Jun. 2018. doi: 10.1109/TII.2018.2817248
    [48]
    X. Huang, W. Lin, and B. Yang, “Global finite-time stabilization of a class of uncertain nonlinear systems,” Automatica, vol. 41, no. 5, pp. 881–888, May 2005. doi: 10.1016/j.automatica.2004.11.036
    [49]
    C. Qian and W. Lin, “Non-Lipschitz continuous stabilizers for nonlinear systems with uncontrollable unstable linearization,” Systems & Control Letters, vol. 42, no. 3, pp. 185–200, Mar. 2001.
    [50]
    R. Olfati-Saber and R. Murray, “Consensus problems in networks of agents with switching topology and time-delays,” IEEE Trans. Automatic Control, vol. 49, no. 9, pp. 1520–1533, Sep. 2004. doi: 10.1109/TAC.2004.834113
    [51]
    Z. Li, G. Wen, Z. Duan, and W. Ren, “Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs,” IEEE Trans. Automatic Control, vol. 60, no. 4, pp. 1152–1157, Apr. 2015. doi: 10.1109/TAC.2014.2350391
    [52]
    P. Sun, B. Zhu, Z. Zuo, and M. V. Basin, “Vision-based finite-time uncooperative target tracking for UAV subject to actuator saturation,” Automatica, vol. 130, p. 109708, Aug. 2021. doi: 10.1016/j.automatica.2021.109708
    [53]
    C. Qian and W. Lin, “A continuous feedback approach to global strong stabilization of nonlinear systems,” IEEE Trans. Automatic Control, vol. 46, no. 7, pp. 1061–1079, Jul. 2001. doi: 10.1109/9.935058
    [54]
    Z. Zuo, M. Defoort, B. Tian, and Z. Ding, “Distributed consensus observer for multiagent systems with high-order integrator dynamics,” IEEE Trans. Automatic Control, vol. 65, no. 4, pp. 1771–1778, Apr. 2020. doi: 10.1109/TAC.2019.2936555
    [55]
    N. T. Dat, C. V. Kien, and H. P. H. Anh, “Optimal FOC-PID parameters of bldc motor system control using parallel pm-pso optimization technique,” Int. Journal of Computational Intelligence Systems, vol. 14, no. 1, pp. 1142–1154, 2021. doi: 10.2991/ijcis.d.210319.001
    [56]
    M. Hu, W. Hua, Z. Wang, S. Li, P. Wang, and Y. Wang, “Selective periodic disturbance elimination using extended harmonic state observer for smooth speed control in pmsm drives,” IEEE Trans. Power Electronics, vol. 37, no. 11, pp. 13288–13298, Nov. 2022. doi: 10.1109/TPEL.2022.3187125

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    Highlights

    • New hyperbolic tangent function-based protocols for achieving finite-time consensus in multi-agent systems, offering a user-prescribed bounded control level with an explicit estimate of the settling time bound
    • Simplified design and stability analysis surpassing traditional saturation function and homogeneity theory approaches
    • Proven effectiveness and practicability via illustrative examples and applications in multi-BLDC motor systems

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