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 9 Issue 8
Aug.  2022

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Y. M. Ju, D. R. Ding, X. He, Q.-L. Han, and G. L. Wei, “Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1440–1451, Aug. 2022. doi: 10.1109/JAS.2021.1004386
 Citation: Y. M. Ju, D. R. Ding, X. He, Q.-L. Han, and G. L. Wei, “Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1440–1451, Aug. 2022.

# Consensus Control of Multi-Agent Systems Using Fault-Estimation-in-the-Loop: Dynamic Event-Triggered Case

##### doi: 10.1109/JAS.2021.1004386
Funds:  This work was supported in part by the Australian Research Council Discovery Early Career Researcher Award (DE200101128)
• The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems (MASs) in the presence of faults. A dynamic event-triggered protocol (DETP) by adding an auxiliary variable is utilized to improve the utilization of communication resources. First, a novel estimator with a noise bias is put forward to estimate the existed fault and then a consensus controller with fault compensation (FC) is adopted to realize the demand of reliability and safety of addressed MASs. Subsequently, a novel consensus control framework with fault-estimation-in-the-loop is developed to achieve the predetermined consensus performance with the $l_{2}$-$l_{\infty}$ constraint by employing the variance analysis and the Lyapunov stability approaches. Furthermore, the desired estimator and controller gains are obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way, respectively. Finally, a simulation result is employed to verify the usefulness of the proposed design framework.

•  [1] A. Isidori, L. Marconi, and G. Casadei, “Robust output synchronization of a network of heterogeneous nonlinear agents via nonlinear regulation theory,” IEEE Trans. Automatic Control, vol. 59, no. 10, pp. 2680–2691, Oct. 2014. [2] J. Qin, Q. Ma, Y. Shi, and L. Wang, “Recent advances in consensus of multi-agent systems: A brief survey,” IEEE Trans. Industrial Electronics, vol. 64, no. 6, pp. 4972–4983, Jun. 2017. [3] H. Song, D. Ding, H. Dong, and X. Yi, “Distributed filtering based on Cauchy-kernel-based maximum correntropy subject to randomly occurring cyber-attacks,” Automatica, vol.135, Article No. 110004, Jan. 2022. [4] X. Wang, D. Ding, H. Dong, and X.-M. Zhang, “Neural-network-based control for discrete-time nonlinear systems with input saturation under stochastic communication protocol,” IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 4, pp. 766–778, Aug. 2021. [5] G. Wen, Z. Duan, G. Chen, and W. Yu, “Consensus tracking of multi-agent systems with Lipschitz-type node dynamics and switching topologies,” IEEE Trans. Circuits and Systems, vol. 61, no. 2, pp. 499–511, Feb. 2014. [6] W. He, Z. Mo, Q.-L. Han, and F. Qian, “Secure impulsive synchronization in Lipschitz-type multi-agent systems subject to deception attacks,” IEEE/CAA Journal of Automatica Sinica, vol. 7, no. 5, pp. 1326–1334, Sep. 2020. [7] Z. Liu, A. Saberi, A. Stoorvogel, and D. Nojavanzadeh, “Global regulated state synchronization for homogeneous networks of non-introspective agents in presence of input saturation: Scale-free nonlinear and linear protocol designs,” Automatica, vol. 119, Article No. 109041, Sep. 2020. [8] Q. Wei, X. Wang, X. Zhong, and N. Wu, “Consensus control of leader-following multi-agent systems in directed topology with heterogeneous disturbances,” IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 2, pp. 423–431, Feb. 2021. [9] J. Hu, H. Zhang, H. Liu, and X. Yu, “A survey on sliding mode control for networked control systems,” Int. Journal of Systems Science, vol. 52, no. 6, pp. 1129–1147, Jan. 2021. [10] J. Mao, Y. Sun, X. Yi, H. Liu, and D. Ding, “Recursive filtering of networked nonlinear systems: A survey,” Int. Journal of Systems Science, vol. 52, no. 4, pp. 1–19, Jan. 2021. [11] B. Shen, Z. Wang, H. Tan, and H. Chen, “Robust fusion filtering over multisensor systems with energy harvesting constraints,” Automatica, vol. 131, Article No. 109782, Sep. 2021. [12] P. Shi, H. Wang, and C. Lim, “Network-based event-triggered control for singular systems with quantizations,” IEEE Trans. Industrial Electronics, vol. 63, no. 2, pp. 1230–1238, Feb. 2016. [13] M. Wang, Z. Wang, Y. Chen, and W. Sheng, “Event-based adaptive neural tracking control for discrete-time stochastic nonlinear systems: A triggering threshold compensation strategy,” IEEE Trans. Neural Networks and Learning Systems, vol. 31, no. 6, pp. 1968–1981, Jun. 2020. [14] Y. Xu, R. Lu, P. Shi, H. Li, and S. Xie, “Finite-time distributed state estimation over sensor networks with round-robin protocol and fading channels,” IEEE Trans. Cybernetics, vol. 48, no. 1, pp. 336–345, Jan. 2018. [15] D. V. Dimarogonas, E. Frazzoli, and K. H. Johansson, “Distributed event-triggered control for multi-agent systems,” IEEE Trans. Automatic Control, vol. 57, no. 5, pp. 1291–1297, May 2012. [16] L. Zou, Z. Wang, J. Hu, and D. H. Zhou, “Moving horizon estimation with unknown inputs under dynamic quantization effects,” IEEE Trans. Automatic Control, vol. 65, no. 12, pp. 5368–5375, Dec. 2020. [17] J. Wang, Z. Duan, G. Wen, and G. Chen, “Distributed robust control of uncertain linear multi-agent systems,” Int. Journal of Robust Nonlinear Control, vol. 25, no. 13, pp. 2162–2179, Sep. 2015. doi: 10.1002/rnc.3199 [18] V. S. Dolk, D. P. Borgers, and W. P. M. H. Heemels, “Output-based and decentralized dynamic event-triggered control with guaranteed Lp-gain performance and zeno-freeness,” IEEE Trans. Automatic Control, vol. 62, no. 1, pp. 34–49, Jan. 2017. [19] X. Ge and Q.-L. Han, “Distributed formation control of networked multi-agent systems using a dynamic event-triggered communication mechanism,” IEEE Trans. Industrial Electronics, vol. 64, no. 10, pp. 8118–8127, Oct. 2017. [20] 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 Journal of Automatica Sinica, vol. 8, no. 5, pp. 971–986, May 2021. [21] Q. Li, B. Shen, Z. Wang, T. Huang, and J. Luo, “Synchronization control for a class of discrete time-delay complex dynamical networks: A dynamic event-triggered approach,” IEEE Trans. Cybernetics, vol. 49, no. 5, pp. 1979–1986, May 2019. [22] S. Xiao and J. Dong, “Distributed fault-tolerant containment control for linear heterogeneous multiagent systems: A hierarchical design approach,” IEEE Trans. Cybernetics, vol. 52, no. 2, pp. 971–981, Feb. 2022. [23] C. Liu, B. Jiang, R. J. Patton, and K. Zhang, “Decentralized output sliding-mode fault-tolerant control for heterogeneous multiagent systems,” IEEE Trans. Cybernetics, vol. 50, no. 12, pp. 4934–4945, Dec. 2020. [24] S. Yin, H. Yang, and O. Kaynak, “Sliding mode observer-based FTC for Markovian jump systems with actuator and sensor faults,” IEEE Trans. Automatic Control, vol. 62, no. 7, pp. 3551–3558, Jul. 2017. [25] J. Zhu, G.-H. Yang, W.-A. Zhang, and L. Yu, “Cooperative fault tolerant tracking control for multiagent systems: An intermediate estimator-based approach,” IEEE Trans. Cybernetics, vol. 48, no. 10, pp. 2972–2980, Oct. 2018. [26] M. Blanke and J. S. Thomsen, “Electrical steering of vehicles-fault-tolerant analysis and design,” Microelectronics Reliability, vol. 46, no. 9, pp. 1421–1432, 2006. [27] Y. Ju, G. Wei, D. Ding, and S. Liu, “Finite-horizon fault estimation for time-varying systems with multiple fading measurements under torus-event-based protocols,” Int. Journal of Robust and Nonlinear Control, vol. 29, no. 13, pp. 4594–4608, Sep. 2019. doi: 10.1002/rnc.4640 [28] F. Boem, A. J. Gallo, D. M. Raimondo, and T. Parisini, “Distributed fault-tolerant control of large-scale systems: An active fault diagnosis approach,” IEEE Trans. Control of Network Systems, vol. 7, no. 1, pp. 288–301, Mar. 2020. [29] L. Li, H. Luo, S. X. Ding, Y. Yang, and K. Peng, “Performance-based fault detection and fault-tolerant control for automatic control systems,” Automatica, vol. 99, pp. 308–316, Jan. 2019. [30] Z. Liang and G.-H. Yang, “Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks,” Information Sciences, vol. 526, pp. 39–53, Jul. 2020. [31] Y. Wang, J. Xia, Z. Wang, and H. Shen, “Design of a fault-tolerant output-feedback controller for thickness control in cold rolling mills,” Applied Mathematics and Computation, vol. 369, Article No. 124841, Mar. 2020. [32] J. Wang, K. Liang, X. Huang, Z. Wang, and H. Shen, “Dissipative fault-tolerant control for nonlinear singular perturbed systems with Markov jumping parameters based on slow state feedback,” Applied Mathematics and Computation, vol. 328, pp. 247–262, Jul. 2018. [33] Q. Liu, Z. Wang, X. He, and D. Zhou, “Event-based recursive distributed filtering over wireless sensor networks,” IEEE Trans. Automatic Control, vol. 60, no. 9, pp. 2470–2475, Sep. 2015. [34] B. Shen, Z. Wang, D. Wang, and H. Liu, “Distributed state-saturated recursive filtering over sensor networks under roundrobin protocol,” IEEE Trans. Cybernetics, vol. 50, no. 8, pp. 3605–3615, Aug. 2020. [35] L. Zou, Z. Wang, H. Geng and X. Liu, “Set-membership filtering subject to impulsive measurement outliers: a recursive algorithm,” IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 2, pp. 377–388, Feb. 2021. [36] D. Zhang, G. Feng, Y. Shi, and D. Srinivasan, “Physical safety and cyber security analysis of multi-agent systems: A survey of recent advances,” IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 2, pp. 319–333, 2021.

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