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Distributed event-triggered generalized Nash equilibrium seeking for aggregative games on unbalanced digraphs

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper addresses the problem of seeking generalized Nash equilibrium for constrained aggregative games with double-integrator agents who communicate with each other on an unbalanced directed graph. An auxiliary variable is introduced to balance the consensus terms in the designed algorithm by estimating the left eigenvector of the Laplacian matrix associated with the zero eigenvalue in a distributed manner. Moreover, an event-triggered broadcasting scheme is proposed to reduce communication loads in the network. It is shown that the proposed communication scheme is free of the Zeno behavior and the asymptotic convergence of the designed algorithm is obtained. Simulation results are demonstrated to validate the proposed methods.
Rocznik
Strony
783--800
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wzory
Twórcy
autor
  • School of Electrical Engineering, Xinjiang University, Urumqi 830047, China
autor
  • School of Electrical Engineering, Xinjiang University, Urumqi 830047, China
autor
  • School of Electrical Engineering, Xinjiang University, Urumqi 830047, China
Bibliografia
  • [1] P. Zhou, W. Wei, K. Bian, D. Wu, Y. Hu and Q. Wang: Private and truthful 230 aggregative game for large-scale spectrum sharing. IEEE Journal on Selected Areas in Communications, 35(2), (2017), 463-477. DOI: 10.1109/JSAC.2017.2659099.
  • [2] Y. Wan, J. Qin, F. Li, X. Yu and Y. Kang: Game theoretic-based distributed charging strategy for pevs in a smart charging station. IEEE 235 Transactions on Smart Grid, 12(1), (2021), 538-547. DOI: 10.1109/TSG.2020.3020466.
  • [3] Z. Liu, Q. Wu, S. Huang, L. Wang, M. Shahidehpour and Y. Xue: Optimal day-ahead charging scheduling of electric vehicles through an aggregative game model. IEEE Transactions on Smart Grid, 9(5), (2018), 5173-5184. DOI: 10.1109/TSG.2017.2682340.
  • [4] C. Sun and G. Hu: Continuous-time penalty methods for nash equilibrium seeking of a nonsmooth generalized noncooperative game. IEEE Transactions on Automatic Control, 6610, (2021), 4895-4902. DOI: 10.1109/TAC.2020.3040377.
  • [5] X. Ai and L. Wang: Distributed adaptive nash equilibrium seeking and disturbance rejection for noncooperative games of high-order nonlinear systems with input saturation and input delay. International Journal of Robust and Nonlinear Control, 31(7), (2021), 2827-2846. DOI: 10.1002/rnc.5418.
  • [6] R. Li and X. Mu: Event-triggered distributed algorithm for searching general nash equilibrium with general step-size. Optimal Control Applications and Methods, 42(2), (2021), 526-547. DOI: 10.1002/oca.2688.
  • [7] X. Cai, F. Xiao and B. Wei: Distributed generalized nash equilibrium seeking for noncooperative games with unknown cost functions. International Journal of Robust and Nonlinear Control, 32(16), (2022), 8948-8964. DOI: 10.1002/rnc.6314.
  • [8] X. Cai, F. Xiao and B. Wei: Distributed strategy-updating rules for aggregative games of multi-integrator systems with coupled constraints. Systems & Control Letters, 170 (2022), 105401. DOI: 10.1016/j.sysconle.2022.105401.
  • [9] K. Lu, G. Jing and L. Wang: Distributed algorithms for searching generalized nash equilibrium of noncooperative games. IEEE Transactions on Cybernetics, 49(6), (2019), 2362-2371. DOI: 10.1109/TCYB.2018.2828118.
  • [10] Z. Deng and S. Liang: Distributed algorithms for aggregative games of multiple heterogeneous Euler-Lagrange systems. Automatica, 99, (2019), 246-252. DOI: 10.1016/j.automatica.2018.10.041.
  • [11] Y. Zhang, S. Liang, X. Wang and H. Ji: Distributed Nash equilibrium seeking for aggregative games with nonlinear dynamics under external disturbances. IEEE Transactions on Cybernetics, 50(12), (2020), 4876-4885. DOI: 10.1109/TCYB.2019.2929394.
  • [12] C. Persis and S. Grammatico: Continuous-time integral dynamics for a class of aggregative games with coupling constraints. IEEE Transactions on Automatic Control, 65(5), (2020), 2171-2176. DOI: 10.1109/TAC.2019.2939639.
  • [13] G. Belgioioso, A. Nedic and S. Grammatico: Distributed generalized Nash equilibrium seeking in aggregative games on time-varying networks. IEEE Transactions on Automatic Control, 66(5), (2021), 2061-2075. DOI: 10.1109/TAC.2020.3005922.
  • [14] P. Yi and L. Pavel: Distributed generalized nash equilibria computation of monotone games via double-layer preconditioned proximal-point algorithms. IEEE Transactions on Control of Network Systems, 6(1), (2019), 299-311. DOI: 10.1109/TCNS.2018.2813928.
  • [15] G. Chen, X. Zeng, P. Yi and Y. Hong: Distributed algorithm for generalized nash equilibria seeking of network aggregative game. In Proceedings of 2017 36th Chinese Control Conference (CCC), (2017), 11319-11324. DOI: 10.23919/ChiCC.2017.8029163.
  • [16] S. Liang, P. Yi and Y. Hong: Distributed Nash equilibrium seeking for aggregative games with coupled constraints. Automatica, 85, (2017), 179-185. DOI: 10.1016/j.automatica.2017.07.064.
  • [17] Z. Deng and X. Nian: Distributed algorithm design for aggregative games of disturbed multiagent systems over weight-balanced digraphs. International Journal of Robust and Nonlinear Control, 28(17), (2018), 5344-5357. DOI: 10.1002/rnc.4316.
  • [18] S. Sun, F. Chen and W. Ren: Distributed average tracking in weight-unbalanced directed networks. IEEE Transactions on Automatic Control, 66(9), (2020), 4436-4443. DOI: 10.1109/TAC.2020.3046029.
  • [19] A. Cortés and S. Martínez: Self-triggered best-response dynamics for continuous games. IEEE Transactions on Automatic Control, 60(4), (2015), 1115-1120. DOI: 10.1109/TAC.2014.2344292.
  • [20] X. Cai, F. Xiao and B.Wei: A distributed strategy-updating rule with eventtriggered communication for noncooperative games. In Proceedings of 39th Chinese Control Conference, (2020), 4747-4752.
  • [21] X. Cai, X. Nan and B. Gao: Distributed adaptive generalized Nash equilibrium seeking algorithm with event-triggered communication. Asian Journal of Control, (2022), 1-10. DOI: 10.0112/asjc.2904.
  • [22] Y. Zhu, W. Yu, G. Wen and G. Chen: Distributed nash equilibrium seeking in an aggregative game on a directed graph. IEEE Transactions on Automatic Control, 66(6), (2021), 2746-2753. DOI: 10.1109/TAC.2020.3008113.
  • [23] C. Godsil and G. Royle: Algebraic Graph Theory. Springer, New York, USA, 2001.
  • [24] Z. Li and Z. Duan: Cooperative Control of Multi-Agent Systems: A Consensus Region Approach. CRC Press, Boca Raton, 2017.
  • [25] F. Facchinei and C. Kanzow: Generalized Nash euqilibrium problems. Annals of Operations Research, 175, (2010), 177-211. DOI: 10.1007/s10479-009-0653-x.
  • [26] Z. Jiang and T. Liu: Small-gain theory for stability and control of dynamical networks: A survey. Annual Reviews in Control, 46 (2018), 58-79. DOI: 10.1016/j.arcontrol.2018.09.001.
  • [27] H. Khalil: Nonlinear Systems. 3rd Edition, Prentice-Hall, USA, 2002.
  • [28] S. Xue, B. Luo and D. Liu: Event-triggered adaptive dynamic programming for zero-sum game of partially unknown continuous-time nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(9), (2020), 3189-3199. DOI: 10.1109/TSMC.2018.2852810.
Uwagi
1. This work was supported by the National Natural Science Foundation of China (NSFC, Grant Nos. 61863033 and 52065064) and by the 2022 Natural Science Foundation of Xinjiang Province.
2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b49310c3-ec34-486b-974b-283eeb62f21c
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