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Volume 8 Issue 11
Nov.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Qingsong Liu, "Pseudo-Predictor Feedback Control for Multiagent Systems with Both State and Input Delays," IEEE/CAA J. Autom. Sinica, vol. 8, no. 11, pp. 1827-1836, Nov. 2021. doi: 10.1109/JAS.2021.1004180
Citation: Qingsong Liu, "Pseudo-Predictor Feedback Control for Multiagent Systems with Both State and Input Delays," IEEE/CAA J. Autom. Sinica, vol. 8, no. 11, pp. 1827-1836, Nov. 2021. doi: 10.1109/JAS.2021.1004180

Pseudo-Predictor Feedback Control for Multiagent Systems with Both State and Input Delays

doi: 10.1109/JAS.2021.1004180
Funds:  This work was supported in part by the National Natural Science Foundation of China (61903282, 61625305) and China Postdoctoral Science Foundation (2020T130488)
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  • This paper is concerned with the consensus problem for high-order continuous-time multiagent systems with both state and input delays. A novel approach referred to as pseudo-predictor feedback protocol is proposed. Unlike the predictor-based feedback protocol which utilizes the open-loop dynamics to predict the future states, the pseudo-predictor feedback protocol uses the closed-loop dynamics of the multiagent systems to predict the future agent states. Full-order/reduced-order observer-based pseudo-predictor feedback protocols are proposed, and it is shown that the consensus is achieved and the input delay is compensated by the proposed protocols. Necessary and sufficient conditions guaranteeing the stability of the integral delay systems are provided in terms of the stability of the series of retarded-type time-delay systems. Furthermore, compared with the existing predictor-based protocols, the proposed pseudo-predictor feedback protocol is independent of the input signals of the neighboring agents and is easier to implement. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approaches.

     

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  • [1]
    I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Comm. Magazine, vol. 40, no. 8, pp. 102–114, 2002. doi: 10.1109/MCOM.2002.1024422
    [2]
    L. Xing, Y. Mishra, Y. C. Tian, G. Ledwich, H. Su, C. Peng, and M. Fei, “Dual-consensus-based distributed frequency control for multiple energy storage systems,” IEEE Trans. Smart Grid, vol. 10, no. 6, pp. 6396–6403, 2019. doi: 10.1109/TSG.2019.2904075
    [3]
    M. Ye, M. H. Trinh, Y. H. Lim, B. D. Anderson, and H. S. Ahn, “Continuous-time opinion dynamics on multiple interdependent topics,” Automatica, vol. 115, Article No. 108884, 2020. doi: 10.1016/j.automatica.2020.108884
    [4]
    R. Olfati-Saber and R. M. Murray, “Consensus problems in networks of agents with switching topology and time-delays,” IEEE Trans. Automatic Control, vol. 49, no. 9, pp. 1520–1533, 2004. doi: 10.1109/TAC.2004.834113
    [5]
    M. Cao, A. S. Morse, and B. D. Anderson, “Reaching a consensus in a dynamically changing environment: A graphical approach,” SIAM J. Control Optimization, vol. 47, no. 2, pp. 575–600, 2008. doi: 10.1137/060657005
    [6]
    S. Izumi, S. I. Azuma, and T. Sugie, “On a relation between graph signal processing and multi-agent consensus,” in Proc. 55th Conf. Decision and Control, 2016, pp. 957–961.
    [7]
    A. Elahi, A. Alfi, and H. Modares, “H consensus control of discretetime multi-agent systems under network imperfections and external disturbance,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 667–675, 2019. doi: 10.1109/JAS.2019.1911474
    [8]
    M. Zhu and S. Martłnez, “Discrete-time dynamic average consensus,” Automatica, vol. 46, no. 2, pp. 322–329, 2010. doi: 10.1016/j.automatica.2009.10.021
    [9]
    S. I. Azuma, Y. Tanaka, and T. Sugie, “Multi-agent consensus under a communication-broadcast mixed environment,” Int. J. Control, vol. 87, no. 6, pp. 1103–1116, 2014. doi: 10.1080/00207179.2013.868608
    [10]
    H. Chu, J. Chen, Q. Wei, and W. Zhang, “Gain scheduling consensus of multi-agent systems subject to actuator saturation,” Int. J. Control, vol. 93, no. 4, pp. 771–782, 2020. doi: 10.1080/00207179.2018.1487079
    [11]
    Y. Su, Q. Wang, and C. Sun, “Self-triggered consensus control for linear multi-agent systems with input saturation,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 150–157, 2020. doi: 10.1109/JAS.2019.1911837
    [12]
    H. Wang, W. Yu, W. Ren, and J. Lü, “Distributed adaptive finite-time consensus for second-order multiagent systems with mismatched disturbances under directed networks,” IEEE Trans. Cybernetics, vol. 51, no. 3, pp. 1347–1358, 2021. doi: 10.1109/TCYB.2019.2903218
    [13]
    W. Yu, G. Chen, and M. Cao, “Some necessary and sufficient conditions for second-order consensus in multi-agent dynamical systems,” Automatica, vol. 46, no. 6, pp. 1089–1095, 2010. doi: 10.1016/j.automatica.2010.03.006
    [14]
    A. Wang, X. Liao, and H. He, “Event-triggered differentially private average consensus for multi-agent network,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 75–83, 2019. doi: 10.1109/JAS.2019.1911327
    [15]
    T. Wang, M. Hu, and Y. Zhao, “Consensus control with a constant gain for discrete-time binary-valued multi-agent systems based on a projected empirical measure method,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 4, pp. 1052–1059, 2019. doi: 10.1109/JAS.2019.1911594
    [16]
    Y. Tian, H. Yan, H. Zhang, X. Zhan, and Y. Peng, “Resilient static output feedback control of linear semi-Markov jump systems with incomplete semi-Markov kernel,” IEEE Transactions on Automatic Control, to be published, 2020.
    [17]
    C. Wang, Z. Zuo, Z. Qi, and Z. Ding, “Predictor-based extended-stateobserver design for consensus of MASs with delays and disturbances,” IEEE Trans. Cybernetics, vol. 49, no. 4, pp. 1259–1269, 2019. doi: 10.1109/TCYB.2018.2799798
    [18]
    A. Ponomarev, Z. Chen, and H. T. Zhang, “Discrete-time predictor feedback for consensus of multiagent systems with delays,” IEEE Trans. Autom. Control, vol. 63, no. 2, pp. 498–504, 2018. doi: 10.1109/TAC.2017.2722860
    [19]
    Y. Zhao and W. Zhang, “Disturbance observer-based consensus control of input-delayed LTI systems with matched disturbances: A predictor feedback approach,” IET Control Theory &Applications, vol. 12, no. 11, pp. 1584–1591, 2018.
    [20]
    C. Wang, Z. Zuo, Z. Lin, and Z. Ding, “Consensus control of a class of Lipschitz nonlinear systems with input delay,” IEEE Trans. Circuits and Systems I:Regular Papers, vol. 62, no. 11, pp. 2730–2738, 2015. doi: 10.1109/TCSI.2015.2479046
    [21]
    H. Chu, D. Yue, C. Dou, X. Xie, and L. Chu, “Consensus of multiagent systems with time-varying input delay via truncated predictor feedback,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, to be published, 2020.
    [22]
    C. Tan, X. Yin, G. P. Liu, J. Huang, and Y. B. Zhao, “Prediction-based approach to output consensus of heterogeneous multi-agent systems with delays,” IET Control Theory &Applications, vol. 12, no. 1, pp. 20–28, 2018.
    [23]
    X. Yang and B. Zhou, “Consensus of discrete-time multiagent systems with input delays by truncated pseudo-predictor feedback,” IEEE Trans. Cybernetics, vol. 49, no. 2, pp. 505–516, 2019. doi: 10.1109/TCYB.2017.2779120
    [24]
    Z. Zuo, C. Wang, and Z. Ding, “Robust consensus control of uncertain multi-agent systems with input delay: A model reduction method,” Int. J. Robust and Nonlinear Control, vol. 27, no. 11, pp. 1874–1894, 2017. doi: 10.1002/rnc.3642
    [25]
    Y. Tian and C. Liu, “Robust consensus of multi-agent systems with diverse input delays and asymmetric interconnection perturbations,” Automatica, vol. 45, pp. 1347–1353, 2009. doi: 10.1016/j.automatica.2009.01.009
    [26]
    Z. Wang, H. Zhang, M. Fu, and H. Zhang, “Consensus for high-order multi-agent systems with communication delay,” Science China Information Sciences, vol. 60, no. 9, Article No. 092204, 2017. doi: 10.1007/s11432-016-0094-7
    [27]
    S. Mondie and W. Michiels, “Finite spectrum assignment of unstable timedelay systems with a safe implementation,” IEEE Trans. Autom. Control, vol. 48, no. 12, pp. 2207–2212, 2003. doi: 10.1109/TAC.2003.820147
    [28]
    B. Zhou and Z. Lin, “Consensus of high-order multi-agent systems with large input and communication delays,” Automatica, vol. 50, no. 2, pp. 452–464, 2014. doi: 10.1016/j.automatica.2013.12.006
    [29]
    B. Zhou, “Consensus of delayed multi-agent systems by reduced-order observer-based truncated predictor feedback protocols,” IET Control Theory &Applications, vol. 8, no. 16, pp. 1741–1751, 2014.
    [30]
    Q. Liu and B. Zhou, “Consensus of discrete-time multi-agent systems with state, input and communication delays,” IEEE Trans. Syst. Man Cybernetics:Syst., vol. 50, no. 11, pp. 4425–4437, 2020. doi: 10.1109/TSMC.2018.2852944
    [31]
    Q. Liu, “Observer-predictor feedback for consensus of discrete-time multiagent systems with both state and input delays,” Int. J. Robust and Nonlinear Control, vol. 30, no. 10, pp. 4003–4021, 2020. doi: 10.1002/rnc.4977
    [32]
    W. Ren and Y. Cao, Distributed Coordination of Multi-Agent Networks (Communications and Control Engineering). London, UK: Springer Verlag, 2011.
    [33]
    B. Zhou, Q. Liu, and F. Mazenc, “Stabilization of linear systems with both input and state delays by observer-predictors,” Automatica, vol. 83, pp. 368–377, 2017. doi: 10.1016/j.automatica.2017.06.027
    [34]
    P. Cui and C. Zhang, “Observer design and output feedback stabilization for linear singular time-delay systems with unknown inputs,” J. Control Theory and Applications, vol. 6, no. 2, pp. 177–183, 2008. doi: 10.1007/s11768-008-6021-6
    [35]
    B. Zhou, “Pseudo-predictor feedback stabilization of linear systems with time-varying input delays,” Automatica, vol. 50, no. 11, pp. 2861–2871, 2014. doi: 10.1016/j.automatica.2014.08.036
    [36]
    J. K. Hale, Theory of Functional Differential Equations. New York USA: Springer, 1977.

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    Highlights

    • Pseudo-predictor based state feedback protocol was proposed for the multiagent systems with state and input delays
    • Full-order observer-based pseudo-predictor feedback protocols and reduced-order observer-based pseudo-predictor feedback protocols were proposed
    • It was shown that the consensus was achieved and the input delay was compensated by the proposed protocols.
    • Compared with the existing predictor-based protocols, the proposed pseudo-predictor feedback protocol is independent of the input signals of the neighboring agents and is easier to implement

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