IEEE/CAA Journal of Automatica Sinica
Citation: | X. Jiang, X. L. Zeng, J. Sun, J. Chen, and Y. Wei, “A fully distributed hybrid control framework for non-differentiable multi-agent optimization,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 10, pp. 1792–1800, Oct. 2022. doi: 10.1109/JAS.2022.105872 |
[1] |
R. R. Li and G. H. Yang, “Distributed optimization for a class of uncertain mimo nonlinear multi-agent systems with arbitrary relative degree,” Inf. Sci., vol. 506, pp. 58–77, Jan. 2020. doi: 10.1016/j.ins.2019.08.010
|
[2] |
Z. H. Zhu, Q. W. Li, X. S. Yang, G. G. Tang, and M. B. Wakin, “Distributed low-rank matrix factorization with exact consensus,” in Proc. 33rd Int. Conf. Neural Information Processing Systems, Vancouver, Canada, 2019, pp. 756.
|
[3] |
H. C. Xiao, D. R. Ding, H. L. Dong, and G. L. Wei, “Adaptive event-triggered state estimation for large-scale systems subject to deception attacks,” Sci. China Inf. Sci., vol. 65, no. 2, p. 122207, Jan. 2022.
|
[4] |
S. C. Swar, S. Manickam, D. Casbeer, K. Kalyanam, and S. Darbha, “Optimal autonomous pursuit of an intruder on a grid aided by local node and edge sensors,” Unmanned Syst., vol. 10, no. 1, pp. 93–108, Jan. 2022. doi: 10.1142/S2301385022500054
|
[5] |
J. Chen, J. Sun, and G. Wang, “From unmanned systems to autonomous intelligent systems,” Engineering, vol. 12, no. 5, pp. 16–19, May 2022.
|
[6] |
M. H. Wang, L. Li, Q. Z. Dai, and F. N. Shi, “Resource allocation based on DEA and non-cooperative game,” J. Syst. Sci. Complex., vol. 34, no. 6, pp. 2231–2249, Dec. 2021. doi: 10.1007/s11424-021-0259-1
|
[7] |
T. Wang, D. O’Neill, and H. Kamath, “Dynamic control and optimization of distributed energy resources in a microgrid,” IEEE Trans. Smart Grid, vol. 6, no. 6, pp. 2884–2894, Nov. 2015. doi: 10.1109/TSG.2015.2430286
|
[8] |
S. Bandyopadhyay and S. J. Chung, “Distributed Bayesian filtering using logarithmic opinion pool for dynamic sensor networks,” Automatica, vol. 97, pp. 7–17, Nov. 2018. doi: 10.1016/j.automatica.2018.07.013
|
[9] |
Z. X. Liu, Y. Z. Yuan, X. P. Guan, and X. B. Li, “An approach of distributed joint optimization for cluster-based wireless sensor networks,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 3, pp. 267–273, Jul. 2015. doi: 10.1109/JAS.2015.7152660
|
[10] |
J. K. Wu, Y. F. Wang, Z. K. Shen, L. Wang, H. P. Du, and C. L. Yin, “Distributed multilane merging for connected autonomous vehicle platooning,” Sci. China Inf. Sci., vol. 64, no. 11, p. 212202, Oct. 2021.
|
[11] |
S. Khan, M. Tufail, M. T. Khan, Z. A. Khan, J. Iqbal, and A. Wasim, “A novel framework for multiple ground target detection, recognition and inspection in precision agriculture applications using a UAV,” Unmanned Syst., vol. 10, no. 1, pp. 45–56, Jan. 2022. doi: 10.1142/S2301385022500029
|
[12] |
S. F. Yang, Q. S. Liu, and J. Wang, “Distributed optimization based on a multiagent system in the presence of communication delays,” IEEE Trans. Syst.,Man,Cybern.: Syst., vol. 47, no. 5, pp. 717–728, May 2017. doi: 10.1109/TSMC.2016.2531649
|
[13] |
A. Nedic, A. Ozdaglar, and P. A. Parrilo, “Constrained consensus and optimization in multi-agent networks,” IEEE Trans. Autom. Control, vol. 55, no. 4, pp. 922–938, Apr. 2010. doi: 10.1109/TAC.2010.2041686
|
[14] |
A. Nedić, A. Olshevsky, and W. Shi, “Achieving geometric convergence for distributed optimization over time-varying graphs,” SIAM J. Optim., vol. 27, no. 4, pp. 2597–2633, Jan. 2017. doi: 10.1137/16M1084316
|
[15] |
R. H. Yang, L. Liu, and G. Feng, “An overview of recent advances in distributed coordination of multi-agent systems,” Unmanned Syst., vol. 10, no. 3, pp. 307–325, Jul. 2022. doi: 10.1142/S2301385021500199
|
[16] |
X. X. Ren, D. W. Li, Y. G. Xi, and H. B. Shao, “Distributed subgradient algorithm for multi-agent optimization with dynamic stepsize,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 8, pp. 1451–1464, Aug. 2021. doi: 10.1109/JAS.2021.1003904
|
[17] |
L. P. Mo, Y. G. Yu, G. J. Ren, and X. L. Yuan, “Constrained consensus of continuous-time heterogeneous multi-agent networks with nonconvex constraints and delays,” J. Syst. Sci. Complex., vol. 35, no. 1, pp. 105–122, Feb. 2022. doi: 10.1007/s11424-021-0092-6
|
[18] |
B. Gharesifard and J. Cortés, “Distributed continuous-time convex optimization on weight-balanced digraphs,” IEEE Trans. Autom. Control, vol. 59, no. 3, pp. 781–786, Mar. 2014. doi: 10.1109/TAC.2013.2278132
|
[19] |
S. Liang, X. L. Zeng, and Y. G. Hong, “Distributed nonsmooth optimization with coupled inequality constraints via modified Lagrangian function,” IEEE Trans. Autom. Control, vol. 63, no. 6, pp. 1753–1759, Jun. 2018. doi: 10.1109/TAC.2017.2752001
|
[20] |
Z. R. Qiu, S. Liu, and L. H. Xie, “Distributed constrained optimal consensus of multi-agent systems,” Automatica, vol. 68, pp. 209–215, Jun. 2016. doi: 10.1016/j.automatica.2016.01.055
|
[21] |
X. X. Li, L. H. Xie, and Y. G. Hong, “Distributed continuous-time nonsmooth convex optimization with coupled inequality constraints,” IEEE Trans. Control Netw. Syst., vol. 7, no. 1, pp. 74–84, Mar. 2020. doi: 10.1109/TCNS.2019.2915626
|
[22] |
Z. Li, J. Fang, Y. Tang, and T. W. Huang, “Consensus of linear discrete-time multi-agent systems: A low-gain distributed impulsive strategy,” IEEE Trans. Syst.,Man,Cybern.: Syst., vol. 49, no. 6, pp. 1041–1052, Jun. 2019. doi: 10.1109/TSMC.2017.2692259
|
[23] |
X. G. Tan, J. D. Cao, L. Rutkowski, and G. P. Lu, “Distributed dynamic self-triggered impulsive control for consensus networks: The case of impulse gain with normal distribution,” IEEE Trans. Cybern., vol. 51, no. 2, pp. 624–634, Feb. 2021. doi: 10.1109/TCYB.2019.2924258
|
[24] |
Z. X. Wang, M. R. Fei, D. J. Du, and M. Zheng, “Decentralized event-triggered average consensus for multi-agent systems in CPSs with communication constraints,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 3, pp. 248–257, Jul. 2015. doi: 10.1109/JAS.2015.7152658
|
[25] |
H. Zhang, G. Feng, H. C. Yan, and Q. J. Chen, “Distributed self-triggered control for consensus of multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 1, pp. 40–45, Jan. 2014. doi: 10.1109/JAS.2014.7004618
|
[26] |
Q. Hui, “Hybrid consensus protocols: An impulsive dynamical system approach,” Int. J. Control, vol. 83, no. 6, pp. 1107–1116, May 2010. doi: 10.1080/00207171003586922
|
[27] |
X. F. Chai, J. Liu, Y. Yu, and C. Y. Sun, “Observer-based self-triggered control for time-varying formation of multi-agent systems,” Sci. China Inf. Sci., vol. 64, no. 3, p. 132205, Feb. 2021.
|
[28] |
X. Jiang, X. L. Zeng, J. Sun, and J. Chen, “Distributed hybrid impulsive algorithm with supervisory resetting for nonlinear optimization problems,” Int. J. Robust Nonlinear Control, vol. 31, no. 8, pp. 3230–3247, May 2021. doi: 10.1002/rnc.5451
|
[29] |
X. Jiang, X. L. Zeng, J. Sun, and J. Chen, “Hybrid protocol for distributed non-differentiable extended monotropic optimization,” in Proc. IEEE 16th Int. Conf. Control & Automation, Singapore, 2020, pp. 654–659.
|
[30] |
W. L. He, G. R. Chen, Q. L. Han, and F. Qian, “Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control,” Inf. Sci., vol. 380, pp. 145–158, Feb. 2017. doi: 10.1016/j.ins.2015.06.005
|
[31] |
G. S. Han, D. X. He, Z. H. Guan, B. Hu, T. Li, and R. Q. Liao, “Multi-consensus of multi-agent systems with various intelligences using switched impulsive protocols,” Inf. Sci., vol. 349–350, pp. 188–198, Jul. 2016. doi: 10.1016/j.ins.2016.02.038
|
[32] |
R. Goebel, R. G. Sanfelice, and A. R. Teel, “Hybrid dynamical systems,” IEEE Control Syst. Mag., vol. 29, no. 2, pp. 28–93, Apr. 2009. doi: 10.1109/MCS.2008.931718
|
[33] |
D. P. Bertsekas, Nonlinear Programming. 2nd ed. Belmont, USA: Athena Scientific, 1999.
|
[34] |
A. Seuret, C. Prieur, S. Tarbouriech, A. R. Teel, and L. Zaccarian, “A nonsmooth hybrid invariance principle applied to robust event-triggered design,” IEEE Trans. Autom. Control, vol. 64, no. 5, pp. 2061–2068, May 2019. doi: 10.1109/TAC.2018.2863188
|
[35] |
E. P. Ryan, “An integral invariance principle for differential inclusions with applications in adaptive control,” SIAM J. Control Optim., vol. 36, no. 3, pp. 960–980, May 1998. doi: 10.1137/S0363012996301701
|
[36] |
J. Wang and N. Elia, “Control approach to distributed optimization,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, USA, 2010, pp. 557–561.
|
[37] |
T. Yang, X. L. Yi, J. F. Wu, Y. Yuan, D. Wu, Z. Y. Meng, Y. G. Hong, H. Wang, Z. L. Lin, and K. H. Johansson, “A survey of distributed optimization,” Annu. Rev. Control, vol. 47, pp. 278–305, May 2019. doi: 10.1016/j.arcontrol.2019.05.006
|
[38] |
Z. H. Li, Z. T. Ding, J. Y. Sun, and Z. K. Li, “Distributed adaptive convex optimization on directed graphs via continuous-time algorithms,” IEEE Trans. Autom. Control, vol. 63, no. 5, pp. 1434–1441, May 2018. doi: 10.1109/TAC.2017.2750103
|
[39] |
A. Bacciotti and F. Ceragioli, “Stability and stabilization of discontinuous systems and nonsmooth Lyapunov functions,” ESAIM: COCV, vol. 4, pp. 361–376, Apr. 1999. doi: 10.1051/cocv:1999113
|
[40] |
Y. N. Zhu, W. W. Yu, G. H. Wen, G. R. Chen, and W. Ren, “Continuous-time distributed subgradient algorithm for convex optimization with general constraints,” IEEE Trans. Autom. Control, vol. 64, no. 4, pp. 1694–1701, Apr. 2019. doi: 10.1109/TAC.2018.2852602
|
[41] |
S. F. Yang, Q. S. Liu, and J. Wang, “A multi-agent system with a proportional-integral protocol for distributed constrained optimization,” IEEE Trans. Autom. Control, vol. 62, no. 7, pp. 3461–3467, Jul. 2017. doi: 10.1109/TAC.2016.2610945
|
[42] |
T. Yang, X. L. Yi, J. F. Wu, Y. Yuan, D. Wu, Z. Y. Meng, Y. G. Hong, H. Wang, Z. L. Lin, and K. H. Johansson, “A survey of distributed optimization,” Annu. Rev. Control, vol. 47, pp. 278–305, May 2019. doi: 10.1016/j.arcontrol.2019.05.006
|