Citation: | M. Ye, “On resilience against cyber-physical uncertainties in distributed Nash equilibrium seeking strategies for heterogeneous games,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 1, pp. 1–10, Jan. 2025. |
[1] |
M. Ye and G. Hu, “Game design and analysis for price based demand response: An aggregate game approach,” IEEE Trans. Cybern., vol. 47, no. 3, pp. 720–730, 2017. doi: 10.1109/TCYB.2016.2524452
|
[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 Trans. Smart Grid, vol. 12, no. 1, pp. 538–547, 2021. doi: 10.1109/TSG.2020.3020466
|
[3] |
J. Fink, A. Ribeiro, and V. Kumar, “Robust control for mobility and wireless communication in cyber – Physical systems with application to robot teams,” Proc. IEEE, vol. 100, no. 1, pp. 164–178, 2012. doi: 10.1109/JPROC.2011.2161427
|
[4] |
M. Fernando, R. Senanayake, and M. Swany, “CoCo games: Graphical game-theoretic swarm control for communication-aware coverage,” IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 5966–5973, 2022. doi: 10.1109/LRA.2022.3160968
|
[5] |
C. Messeri, G. Masotti, A. M. Zanchettin, and P. Rocco, “Human-robot collaboration: Optimizing stress and productivity based on game theory,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8061–8068, 2021. doi: 10.1109/LRA.2021.3102309
|
[6] |
M. Ye, Q.-L. Han, L. Ding, and S. Xu, “Distributed Nash equilibrium seeking in games with partial decision information: A survey,” Proc. IEEE, vol. 111, no. 2, pp. 140–157, 2023. doi: 10.1109/JPROC.2023.3234687
|
[7] |
Y. Tang, “Distributed Nash equilibrium seeking algorithms for uncertain linear multi-agent systems,” in Proc. Asian Control Conf., 2022, pp. 2277–2281.
|
[8] |
X. Liu, Y. Zhang, X. Wang, and H. Ji, “Distributed Nash equilibrium seeking design in network of uncertain linear multi-agent systems,” in Proc. IEEE Int. Conf. Control & Automation, 2020, pp. 147–152.
|
[9] |
Y. Zhang, S. Liang, X. Wang, and H. Ji, “Distributed Nash equilibrium seeking for aggregative games with nonlinear dynamics under external disturbances,” IEEE Trans. Cybern., vol. 50, no. 12, pp. 4876–4885, 2020. doi: 10.1109/TCYB.2019.2929394
|
[10] |
X. Nian, F. Niu, and S. Li, “Nash equilibrium seeking for multicluster games of multiple nonidentical Euler–Lagrange systems,” IEEE Trans. Control of Network Systems, vol. 10, no. 4, pp. 1732–1743, 2023. doi: 10.1109/TCNS.2023.3239547
|
[11] |
B. Huang, Z. Meng, and F. Chen, “Distributed nonlinear placement for a class of multicluster Euler–Lagrange systems,” IEEE Trans. Systems, Man, and Cybern.: Systems, vol. 52, no. 10, pp. 6418–6425, 2022. doi: 10.1109/TSMC.2022.3150071
|
[12] |
M. Ye, “Distributed robust seeking of Nash equilibrium for networked games: An extended state observer-based approach,” IEEE Trans. Cybern., vol. 52, no. 3, pp. 1527–1538, 2022. doi: 10.1109/TCYB.2020.2989755
|
[13] |
X.-F. Wang, A. R. Teel, X.-M. Sun, K.-Z. Liu, and G. Shao, “A distributed robust two-time-scale switched algorithm for constrained aggregative games,” IEEE Trans. Autom. Control, vol. 68, no. 11, pp. 6525–6540, 2023. doi: 10.1109/TAC.2023.3240981
|
[14] |
M. Ye, L. Ding, and J. Yin, “Distributed robust Nash equilibrium seeking for mixed-order games by a neural-network-based approach,” IEEE Trans. Systems, Man, and Cybern.: Systems, vol. 50, no. 8, pp. 4808–4819, 2023.
|
[15] |
Y. Tang, and P. Yi, “Nash equilibrium seeking for high-order multiagent systems with unknown dynamics,” IEEE Trans. Control Network Systems, vol. 10, no. 1, pp. 321–332, 2023. doi: 10.1109/TCNS.2022.3203362
|
[16] |
J. Huang, “Distributed Nash equilibrium seeking for a class of uncertain nonlinear systems subject to bounded disturbances,” IEEE Trans. Automatic Control, 2024. DOI 10.1109/TAC.2024.3359525.
|
[17] |
Z. Feng, G. Hu, X. Dong, and J. Lv, “Adaptively distributed Nash equilibrium seeking of noncooperative games for uncertain heterogeneous linear multi-agent systems,” IEEE Trans. Network Science and Engineering, vol. 10, no. 6, pp. 3871–3882, 2023.
|
[18] |
X. Ge, Q.-L. Han, Q. Wu, X.-M. Zhang, “Resilient and safe platooning control of connected automated vehicles against intermittent Denial-of-Service attacks,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1234–1251, 2023. doi: 10.1109/JAS.2022.105845
|
[19] |
X. Gong, M. V. Basin, Z. Feng, T. Huang, and Y. Cui, “Resilient time-varying formation-tracking of multi-UAV systems against composite attacks: A two-layered framework,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 969–984, 2023. doi: 10.1109/JAS.2023.123339
|
[20] |
C. Chen, K. Xie, F. L. Lewis, S. Xie, and R. Fierro, “Adaptive synchronization of multi-agent systems with resilience to communication link faults,” Automatica, vol. 111, p. 108636, 2020. doi: 10.1016/j.automatica.2019.108636
|
[21] |
C. Qian and L. Ding, “Fully distributed attack-resilient Nash equilibrium seeking for networked games subject to DoS attacks,” Information Sciences, vol. 641, p. 119080, 2023. doi: 10.1016/j.ins.2023.119080
|
[22] |
X.-F. Wang, X.-M. Sun, M. Ye, and K.-Z. Liu, “Robust distributed Nash equilibrium seeking for games under attacks and communication delays,” IEEE Trans. Autom. Control, vol. 67, no. 9, pp. 4892–4899, 2022. doi: 10.1109/TAC.2022.3164984
|
[23] |
X. Cai, F. Xiao, and B. Wei, “Resilient Nash equilibrium seeking in multiagent games under false data injection attacks,” IEEE Trans. Systems, Man, and Cybern.: Systems, vol. 53, no. 1, pp. 275–284, 2023. doi: 10.1109/TSMC.2022.3180006
|
[24] |
Y. Cheng, L. Zhang, and S. Liu, “Nash equilibrium strategy in stochastic non-cooperative games,” in Proc. IEEE Int. Conf. Control and Automation, 2020, pp. 530–535.
|
[25] |
X. Fang, G. Wen, J. Zhou, and W. X. Zheng, “Distributed adaptive Nash equilibrium seeking over multi-agent networks with communication uncertainties,” in Proc. IEEE Conf. Decision and Control, 2021, pp. 3387–3392.
|
[26] |
W. Ren and R. W. Beard, Distributed Consensus in Multi-Vehicle Cooperative Control, London UK: Springer London, 2008.
|
[27] |
Z. Li, Z. Wu, Z. Li, and Z. Ding, “Distributed optimal coordination for heterogeneous linear multiagent systems with event-triggered mechanisms,” IEEE Trans. Autom. Control, vol. 65, no. 4, pp. 1763–1770, 2020. doi: 10.1109/TAC.2019.2937500
|
[28] |
H. Khailil, Nonlinear Systems, Upper Saddle River, USA: Prentice Hall, 2002.
|
[29] |
F. Facchinei, and J.-S. Pang, Finite-Dimensional Variational Inequalities and Complementarity Problems, Springer, 2003.
|
[30] |
J. Mei, W. Ren, and Y. Song, “A Unified framework for adaptive leaderless consensus of uncertain multiagent systems under directed graphs,” IEEE Trans. Autom. Control, vol. 66, no. 12, pp. 6179–6186, 2021. doi: 10.1109/TAC.2021.3062594
|
[31] |
M. Ye and G. Hu, “Adaptive approaches for fully distributed Nash equilibrium seeking in networked games,” Automatica, vol. 129, p. 109661, 2021. doi: 10.1016/j.automatica.2021.109661
|
[32] |
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, 2023. doi: 10.1109/JAS.2022.105983
|
[33] |
X. Ge, Q.-L. Han, X.-M. Zhang, and D. Ding, “Communication resource-efficient vehicle platooning control with various spacing policies,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 362–376, 2024. doi: 10.1109/JAS.2023.123507
|
[34] |
L. Zou, Z. Wang, B. Shen, H. Dong, and G. Lu, “Encrypted finitehorizon energy-to-peak state estimation for time-varying systems under eavesdropping attacks: tackling secrecy capacity,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 985–996, 2023. doi: 10.1109/JAS.2023.123393
|
[35] |
L. Zou, Z. Wang, B. Shen, and H. Dong, “Moving horizon estimation over relay channels: Dealing with packet losses,” Automatica, vol. 155, p. 111079, 2023. doi: 10.1016/j.automatica.2023.111079
|
[36] |
L. Zou, Z. Wang, B. Shen, and H. Dong, “Encryption-decryption-based state estimation with multirate measurements against eavesdroppers: A recursive minimumvariance approach,” IEEE Trans. Autom. Control, vol. 68, no. 12, pp. 8111–8118, 2023. doi: 10.1109/TAC.2023.3288624
|