Volume 18, Issue 2 (Journal of Control, V.18, N.2 Summer 2024)                   JoC 2024, 18(2): 69-83 | Back to browse issues page

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Gholami F, Hashemi M, Shahgholian G. Adaptive Observer-Based Consensus of Fractional-Order Multi-Agent Systems in The Presence of Actuator Fault: Event-Triggered Scheme. JoC 2024; 18 (2) :69-83
URL: http://joc.kntu.ac.ir/article-1-1009-en.html
1- Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Abstract:   (1001 Views)
This paper addresses the distributed event-triggered control design for a class of fractional-order strict-feedback uncertain multi-agent systems in the presence of unknown actuator fault by employing backstopping strategy. To reduce the communication burden and unnecessary waste of communication resources, an event-triggered control signal is designed. In the design process, considering that the information of followers’ states is not measurable directly, the fractional-order neural adaptive state observer is introduced to estimate them. The adaptive neural laws are also proposed to eliminate the undesirable effects of the unknown nonlinear functions. Then, an adaptive fault strategy is applied to compensate the loss of actuator faults. Besides, based on the Lyapunov fractional-order stability approach and graph theory, unlike the existing results, a distributed event-triggered adaptive observer-based control architecture is designed to ensure that all the closed-loop network signals are ultimately bounded
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Type of Article: Research paper | Subject: Special
Received: 2023/11/11 | Accepted: 2024/09/5 | ePublished ahead of print: 2024/09/12 | Published: 2024/09/20

References
1. [1] D. Alibeigi, E. Abbaspour, B. Fani, H. Samet, "An intelligent multi-agent based approach for protecting distribution networks", Technovations of Electrical Engineering in Green Energy System, vol. 1, no. 1, pp. 36-62, June 2022.
2. [2] F. Mohammadzamani, M. Hashemi, G. Shahgholian, "Adaptive control of nonlinear time delay systems in the presence of output constraints and actuator's faults", International Journal of Control, vol. 96, no. 3, pp. 541-553, March 2023. [DOI:10.1080/00207179.2021.2005257]
3. [3] K.R. Kumar, S. Maheswarapu, "Optimal power flows with security constraints using cubic lattice structured multi agent based PSO algorithm by optimal placement of multiple TCSCs", Majlesi Journal of Electrical Engineering, vol. 8, no. 4, pp. 1-26, vol. 2014.
4. [4] T. Liu, Z.P. Zhong, "Event-based control of nonlinear systems with partial state and output feedback", Automatica, vol. 53, pp. 10-22, Mar. 2015. [DOI:10.1016/j.automatica.2014.12.027]
5. [5] F. Mohammadzamani, M. Hashemi, G. Shahgholian, "Adaptive control of nonlinear time delay systems in the presence of output constraints", Journal of Intelligent Procedures in Electrical Technology, vol. 10, no. 40, pp. 3-12, Winter 2020.
6. [6] R. Obermaisser, "Event-triggered and time-triggered control paradigms", Springer Science & Business Media, vol. 22, Sept. 2004. [DOI:10.1007/978-0-387-23044-3]
7. [7] W.P.M.H. Heemels, K.H. Johansson, P. Tabuada, "An introduction to event-triggered and self-triggered control", Proceeding of the IEEE/CDC, pp. 3270-3285, Maui, HI, USA, Dec. 2012. [DOI:10.1109/CDC.2012.6425820]
8. [8] J. Sun, J. Yang, S. Li, W.X. Zheng, "Output-based dynamic event-triggered mechanisms for distur¬bance rejection control of networked nonlinear systems", IEEE Trans. on Cybernetics, vol. 50, no. 5, pp. 1978-1988, May. 2020. [DOI:10.1109/TCYB.2018.2877413]
9. [9] X. Ge, Q.L. Han, L. Ding, Y.L. Wang, X.M. Zhang, "Dynamic event-triggered distributed coordination Control and its applications: a survey of trends and techniques", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 50, no. 9, pp. 3112-3125, Sept. 2020. [DOI:10.1109/TSMC.2020.3010825]
10. [10] T.F. Li, J. Fu," Event-triggered control of switched linear systems", Journal of the Franklin Institute, vol. 354, pp. 6451-6462, Oct. 2017. [DOI:10.1016/j.jfranklin.2017.05.018]
11. [11] S. Payandeh-Najafabadi, M. Hashemi, "The adaptive sliding synchronization of uncertain Duffing-Holmes fractional-order chaotic systems with dead-zone", Journal of Vibration and Control, vol. 30, no. 19-20, pp. 4486-4497, Oct. 2024. [DOI:10.1177/10775463231211045]
12. [12] G. Shahgholian, "An overview of hydroelectric power plant: Operation, modeling, and control", Journal of Renewable Energy and Environment, vol. 7, no. 3, pp. 14-28, July 2020.
13. [13] Z. Liu, J. Wang, C. L. P. Chen, Y. Zhang, "Event trigger fuzzy adaptive compensation control of uncertain stochastic nonlinear systems with actuator failures", IEEE Trans. on Fuzzy Systems, vol. 26, no. 6, pp. 3770-3781, Dec. 2018. [DOI:10.1109/TFUZZ.2018.2848909]
14. [14] P. Hernández-León, J. Dávila, S. Salazar, X. Ping, "Distance-based formation maneuvering of non-holonomic wheeled mobile robot multi-agent system", IFAC-PapersOnLine, vol. 53, pp. 5665-5670, Jan. 2020. [DOI:10.1016/j.ifacol.2020.12.1588]
15. [15] H. Liu, P. Weng, X. Tian, Q. Mai, "Distributed adaptive fixed-time formation control for UAV-USV heterogeneous multi-agent systems", Ocean Engineering, vol. 267, pp. 113240, Jan. 2023. [DOI:10.1016/j.oceaneng.2022.113240]
16. [16] Y. Yu, J. Guo, C. K. Ahn and Z. Xiang, "Neural adaptive distributed formation control of nonlinear multi-UAVs with unmodeled dynamics", IEEE Trans. on Neural Networks and Learning Systems, vol. 34, no. 11, pp. 8555-9561, Nov. 2023. [DOI:10.1109/TNNLS.2022.3157079]
17. [17] Z. Peng, D. Wang, Z. Chen, X. Hu and W. Lan, "Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics", IEEE Trans. on Control Systems Technology, vol. 21, no. 2, pp. 513-520, March. 2013. [DOI:10.1109/TCST.2011.2181513]
18. [18] C.E. Ren, L. Chen, C.L.P. Chen, T. Du, "Quantized consensus control for second-order multi-agent systems with nonlinear dynamics", Neurocomputing, vol. 175, pp. 529-540, Jan. 2016. [DOI:10.1016/j.neucom.2015.10.090]
19. [19] C.L.P. Chen, G.X. Wen, Y.J. Liu, F.Y. Wang, "Adaptive consensus control for a class of nonlinear multiagent time-delay systems using neural networks", IEEE Trans. on Neural Networks and Learning Systems, vol. 25, no. 6, pp. 1217-1226, June 2014. [DOI:10.1109/TNNLS.2014.2302477]
20. [20] Z. Zhang, F. Hao, L. Zhang, L. Wang, "Consensus of linear multi-agent systems via event-triggered control", International Journal of Control, vol. 87, pp. 1243-1251, June 2014. [DOI:10.1080/00207179.2013.873952]
21. [21] A. Zhang, D. Zhou, P. Yang, M. Yang, "Event-triggered finite-time consensus with fully continuous communication free for second-order multi-agent systems", International Journal of Control, Automation and Systems, vol. 17, pp. 836-846, April 2019. [DOI:10.1007/s12555-018-0666-9]
22. [22] D. Liu, G.H. Yang, "A dynamic event-triggered control approach to leader-following consensus for linear multiagent systems", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 51, no. 10, pp. 6271-6279, Oct. 2021. [DOI:10.1109/TSMC.2019.2960062]
23. [23] L. Yan, T. Stouraitis and S. Vijayakumar, "Decentralized ability-aware adaptive control for multi-robot collaborative manipulation", IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 2311-2318, April 2021. [DOI:10.1109/LRA.2021.3060379]
24. [24] D. Wang, Q. Zong, B. Tian, F. Wang, L. Dou," Finite‐time fully distributed formation reconfiguration control for UAV helicopters", International Journal of Robust and Nonlinear Control, vol. 28, pp. 5943-5961, Dec. 2018. [DOI:10.1002/rnc.4361]
25. [25] S. Li, X. Wang, " Finite-time consensus and collision avoidance control algorithms for multiple AUVs", Automatica, vol. 49, pp. 3359-3367, Nov. 2013. [DOI:10.1016/j.automatica.2013.08.003]
26. [26] Y. Li, K. Li and S. Tong, "An Observer-Based Fuzzy Adaptive Consensus Control Method for Nonlinear Multiagent Systems", IEEE Trans. on Fuzzy Systems, vol. 30, no. 11, pp. 4667-4678, Nov. 2022. [DOI:10.1109/TFUZZ.2022.3154433]
27. [27] D. Liu, Z. Liu, C. L. P. Chen, Y. Zhang, "Distributed adaptive neural fixed-time tracking control of multiple uncertain mechanical systems with actuation dead zones", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 52, no. 6, pp. 3859-3872, June 2022. [DOI:10.1109/TSMC.2021.3075967]
28. [28] C. Zhou, Y. Wang, M. Lv, N. Wang, "Neural-adaptive specified-time constrained consensus tracking control of high-order nonlinear multi-agent systems with unknown control directions and actuator faults", Neurocomputing, vol. 538, Article Number: 126168, June 2023. [DOI:10.1016/j.neucom.2023.03.029]
29. [29] M. Hashemi, G. Shahgholian, "Distributed robust adaptive control of high order nonlinear multi agent systems", ISA Transactions, vol. 74, pp. 14-27, March 2018. [DOI:10.1016/j.isatra.2018.01.023]
30. [30] I. Doye, H. Voos, M. Darouach, J.G. Schneider, "Static output feedback ℋ∞ control for a fractional-order glucose-insulin system", International Journal of Control, Automation and Systems, vol. 13, pp. 798-807, Aug. 2015. [DOI:10.1007/s12555-013-9192-y]
31. [31] S. Song, B. Zhang, X. Song and Z. Zhang, "Neuro-fuzzy-based adaptive dynamic surface control for fractional-order nonlinear strict-feedback systems with input constraint", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 51, no. 6, pp. 3575-3586, June 2021. [DOI:10.1109/TSMC.2019.2933359]
32. [32] Y. Cao, Y. Li, W. Ren and Y. Chen, "Distributed coordination of networked fractional-order systems", IEEE Trans. on Systems, Man, and Cybernetics, vol. 40, no. 2, pp. 362-370, April 2010. [DOI:10.1109/TSMCB.2009.2024647]
33. [33] T.J. Freeborn, "A survey of fractional-order circuit models for biology and biomedicine", IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 3, no. 3, pp. 416-424, Sept. 2013. [DOI:10.1109/JETCAS.2013.2265797]
34. [34] H.Y. Yang, Y. Yang, F. Han, M. Zhao, L. Guo, "Containment control of heterogeneous fractional-order multi-agent systems", Journal of the Franklin Institute", vol. 356, pp. 752-765, Oct. 2019. [DOI:10.1016/j.jfranklin.2017.09.034]
35. [35] T. Ma, T. Li, B. Cui, "Coordination of fractional-order nonlinear multi-agent systems via distributed impulsive control", International Journal of Systems Science, vol. 49, pp 1-4, Jan. 2018. [DOI:10.1080/00207721.2017.1397805]
36. [36] J. Bai, G. Wen, A. Rahmani, Y. Yu, "Consensus for the fractional-order double-integrator multi-agent systems based on the sliding mode estimator", IET Control Theory and Applications, vol: 12, no. 5, pp 621-628, Dec. 2018. [DOI:10.1049/iet-cta.2017.0523]
37. [37] X. Zhang, S. Zheng, C. K. Ahn and Y. Xie, "Adaptive neural consensus for fractional-order multi-agent systems with faults and delays", IEEE Trans on Neural Networks and Learning Systems, vol. 34, no. 10, pp. 7873-7886, Feb. 2022. [DOI:10.1109/TNNLS.2022.3146889]
38. [38] M.K. Shukla, B.B. Sharma, "Backstepping based stabilization and synchronization of a class of fractional order chaotic systems", Chaos, Solitons & Fractals.vol. 102, pp 274-284, Sept. 2017. [DOI:10.1016/j.chaos.2017.05.015]
39. [39] F. Zouari, A. Ibeas, A. Boulkroune, J. Cao, M.M Arefi, "Neuro-adaptive tracking control of non-integer order systems with input nonlinearities and time-varying output constraints", Information Sciences, vol. 485. no. 24, pp 170-192, June 2019. [DOI:10.1016/j.ins.2019.01.078]
40. [40] S. Song, B. Zhang, J. Xia and Z. Zhang, "Adaptive backstepping hybrid fuzzy sliding mode control for uncertain fractional-order nonlinear systems based on finite-time scheme", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 50, no. 4, pp. 1559-1569, April 2020. [DOI:10.1109/TSMC.2018.2877042]
41. [41] F. Wang, Y. Yang, "Leader-following consensus of nonlinear fractional-order multi-agent systems via event-triggered control", International Journal of Systems Science, vol.48, pp. 571-577, Feb. 2017. [DOI:10.1080/00207721.2016.1193258]
42. [42] M. Shi, S. Hu, Y. Yu," Generalised exponential consensus of the fractional-order nonlinear multi-agent systems via event-triggered control", International Journal of Systems Science, vol. 50, pp. 1244-1251, April 2019. [DOI:10.1080/00207721.2019.1598510]
43. [43] J. Yuan, T. Chen, "Switched fractional order multiagent systems containment control with event-triggered mechanism and input quantization", Fractal and Fractional, vol. 6, no. 2, pp. 77, Jan. 2022. [DOI:10.3390/fractalfract6020077]
44. [44] T. Chen, J. Yuan," Command-filtered adaptive containment control of fractional-order multi-agent systems via event-triggered mechanism", Transa. of the Institute of Measurement and Control, vol. 45, no. 9, pp. 1646-1660, June 2023. [DOI:10.1177/01423312221137618]
45. [45] I. Podlubny, "Fractional differential equation", Academic Press, San Diego.1999.
46. [46] R. Gorenflo, A.A. Kilbas, S.V. Rogosin, "On the generalized mittag-leffler type functions", Integral Transforms and Special function, vol. 7, pp. 215-224, Oct. 1998. [DOI:10.1080/10652469808819200]
47. [47] M. Wei, Y.X. Li, Sh. Tong," Event-triggered adaptive neural control of fractional-order nonlinear systems with full-state constraints", Neurocomputing, vol. 412, pp. 320-326, Oct. 2020. [DOI:10.1016/j.neucom.2020.06.082]
48. [48] X.Y. Zhang, Y.X. Li and J. Sun,"Observer-based robust adaptive neural control for nonlinear multi-agent systems with quantised input.", International Journal of Systems Science, vol. 55, pp. 1270-1282, Jan. 2024. [DOI:10.1080/00207721.2024.2304133]
49. [49] Z. Yongliang, X. Li, S. Tong. "Observer-based decentralized control for non-strict-feedback fractional-order nonlinear large-scale systems with unknown dead zones", IEEE Trans. on Neural Networks and Learning Systems, vol. 34, no. pp. 7479-7490, Oct. 2022. [DOI:10.1109/TNNLS.2022.3143901]
50. [50] H. Lili, H. Yu, X. Xia, "Fuzzy adaptive tracking control of fractional-order multi-agent systems with partial state constraints and input saturation via event-triggered strategy", Information Scienc¬es, vol. 646, Article Number: 119396, Oct. 2023. [DOI:10.1016/j.ins.2023.119396]
51. [51] F. Mohammadzamani, M. Hashemi, G. Shahgho-lian, "Adaptive neural control of non‐linear fractional order multi‐agent systems in the presence of error constraints and input saturation", IET Control Theory and Applications, vol. 16, no. 13, PP. 1283-1298, April 2022. [DOI:10.1049/cth2.12291]
52. [52] W. Chaoyue, Z. Ma, Sh. Tong, "Adaptive fuzzy output-feedback event-triggered control for fractional-order nonlinear system", Mathematical Biosciences and Engineering, vol. 19, no. 12, pp. 12334-12352, Jan. 2022. [DOI:10.3934/mbe.2022575]
53. [53] Y. Liu, H. Zhang, Y. Wang, H. Liang, "Adaptive containment control for fractional-order nonlinear multi- agent systems with time-varying parameters", IEEE/CAA Journal of Automatica Sinica, vol. 9, no. 9, pp. 1627-1638, Sept. 2022. [DOI:10.1109/JAS.2022.105545]

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