Event-triggered design for multi-agent optimal consensus of Euler-Lagrangian systems

Xue-Fang Wang; Zhenhua Deng; Song Ma; Xian Du

Kybernetika (2017)

  • Volume: 53, Issue: 1, page 179-194
  • ISSN: 0023-5954

Abstract

top
In this paper, a distributed optimal consensus problem is investigated to achieve the optimization of the sum of local cost function for a group of agents in the Euler-Lagrangian (EL) system form. We consider that the local cost function of each agent is only known by itself and cannot be shared with others, which brings challenges in this distributed optimization problem. A novel gradient-based distributed continuous-time algorithm with the parameters of EL system is proposed, which takes the distributed event-triggered control mechanism into account. A sufficient condition is given to show that the performance of the global convergence to the optimal point can be guaranteed under the proposed method. Moreover, the Zeno behavior of triggering time can be excluded. Finally, to show the effectiveness of the presented algorithm, an example is given along with simulation results.

How to cite

top

Wang, Xue-Fang, et al. "Event-triggered design for multi-agent optimal consensus of Euler-Lagrangian systems." Kybernetika 53.1 (2017): 179-194. <http://eudml.org/doc/287933>.

@article{Wang2017,
abstract = {In this paper, a distributed optimal consensus problem is investigated to achieve the optimization of the sum of local cost function for a group of agents in the Euler-Lagrangian (EL) system form. We consider that the local cost function of each agent is only known by itself and cannot be shared with others, which brings challenges in this distributed optimization problem. A novel gradient-based distributed continuous-time algorithm with the parameters of EL system is proposed, which takes the distributed event-triggered control mechanism into account. A sufficient condition is given to show that the performance of the global convergence to the optimal point can be guaranteed under the proposed method. Moreover, the Zeno behavior of triggering time can be excluded. Finally, to show the effectiveness of the presented algorithm, an example is given along with simulation results.},
author = {Wang, Xue-Fang, Deng, Zhenhua, Ma, Song, Du, Xian},
journal = {Kybernetika},
keywords = {optimal consensus; multi-agent system; Euler–Lagrangian system; event-triggered control},
language = {eng},
number = {1},
pages = {179-194},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Event-triggered design for multi-agent optimal consensus of Euler-Lagrangian systems},
url = {http://eudml.org/doc/287933},
volume = {53},
year = {2017},
}

TY - JOUR
AU - Wang, Xue-Fang
AU - Deng, Zhenhua
AU - Ma, Song
AU - Du, Xian
TI - Event-triggered design for multi-agent optimal consensus of Euler-Lagrangian systems
JO - Kybernetika
PY - 2017
PB - Institute of Information Theory and Automation AS CR
VL - 53
IS - 1
SP - 179
EP - 194
AB - In this paper, a distributed optimal consensus problem is investigated to achieve the optimization of the sum of local cost function for a group of agents in the Euler-Lagrangian (EL) system form. We consider that the local cost function of each agent is only known by itself and cannot be shared with others, which brings challenges in this distributed optimization problem. A novel gradient-based distributed continuous-time algorithm with the parameters of EL system is proposed, which takes the distributed event-triggered control mechanism into account. A sufficient condition is given to show that the performance of the global convergence to the optimal point can be guaranteed under the proposed method. Moreover, the Zeno behavior of triggering time can be excluded. Finally, to show the effectiveness of the presented algorithm, an example is given along with simulation results.
LA - eng
KW - optimal consensus; multi-agent system; Euler–Lagrangian system; event-triggered control
UR - http://eudml.org/doc/287933
ER -

References

top
  1. Nedic, A., Ozdaglar, A., 10.1109/tac.2008.2009515, IEEE Trans. Automat. Control 54 (2009), 48-61. MR2478070DOI10.1109/tac.2008.2009515
  2. Shi, G., Johansson, K. H., Hong, Y., 10.1109/tac.2012.2215261, IEEE Trans. Automat. Control 58 (2013), 610-622. MR3029459DOI10.1109/tac.2012.2215261
  3. Bose, S., Low, S. H., Teeraratkul, T., Hassibi, B., 10.1109/tac.2014.2357112, IEEE Trans. Automat. Control 60 (2015), 729-742. MR3318399DOI10.1109/tac.2014.2357112
  4. Zhang, Y., Lou, Y., Hong., Y., Xie, L., 10.1109/twc.2015.2402672, IEEE Trans. Wireless Commun. 14 (2015), 3131-3142. DOI10.1109/twc.2015.2402672
  5. Liu, Q., Wang, J., 10.1109/tac.2015.2416927, IEEE Trans. Automat. Control 60 (2015), 3310-3315. MR3432700DOI10.1109/tac.2015.2416927
  6. Yi, P., Hong, Y., Liu, F., 10.1016/j.sysconle.2015.06.006, Systems Control Lett. 83 (2015), 45-52. Zbl1327.93033MR3373270DOI10.1016/j.sysconle.2015.06.006
  7. Wang, X., Yi, P., Hong, Y., 10.1007/s11768-014-0036-y, Control Theory Technol. 12 (2014), 132-138. MR3199533DOI10.1007/s11768-014-0036-y
  8. Wang, X., Hong, Y., Ji, H., 10.1109/tcyb.2015.2453167, IEEE Trans. Cybernet. 46 (2016), 1655-1666. DOI10.1109/tcyb.2015.2453167
  9. Zhang, Y., Deng, Z., Hong, Y., 10.1016/j.automatica.2017.01.004, Automatica 79 (2017), 207-213. MR3627983DOI10.1016/j.automatica.2017.01.004
  10. Yi, P., Hong, Y., 10.1007/s11768-015-5100-8, Control Theory Technol. 13 (2015), 333-347. MR3435158DOI10.1007/s11768-015-5100-8
  11. Hu, J., Chen, G., Li, H., Distributed event-triggered tracking control of leader-follower multi-agent systems with communication delays., Kybernetika 47 (2011), 630-643. Zbl1227.93008MR2884865
  12. Deng, Z., Hong, Y., 10.1109/icca.2016.7505245, In: 12th IEEE Int. Conf. Control and Autom., Kathmandu 2016, pp 13-18. DOI10.1109/icca.2016.7505245
  13. Tabuada, P., 10.1109/tac.2007.904277, IEEE Trans. Automat. Control 52 (2007), 1680-1685. MR2352444DOI10.1109/tac.2007.904277
  14. Chen, W. S., Ren, W., 10.1016/j.automatica.2015.11.015, Automatica 65 (2016), 90-97. Zbl1328.93167MR3447697DOI10.1016/j.automatica.2015.11.015
  15. Deng, Z., Wang, X., Hong, Y., 10.1049/iet-cta.2016.0795, IET Control Theory Appl. 11 (2017), 2, 282-290. DOI10.1049/iet-cta.2016.0795
  16. Kia, S. S., Cortes, J., Martinez, S., 10.1016/j.automatica.2015.03.001, Automatica 55 (2015), 254-264. MR3336675DOI10.1016/j.automatica.2015.03.001
  17. Cai, H., Huang, J., 10.1080/03081079.2014.883714, Int. J. Gene. Sys., 43 (2014), 294-304. Zbl1302.93005MR3177023DOI10.1080/03081079.2014.883714
  18. Chung, S. J., Slotine, J. J. E., 10.1109/tro.2009.2014125, IEEE Trans. Robotics 25 (2009), 686-700. DOI10.1109/tro.2009.2014125
  19. Dixon, W. E., Nonlinear Control of Engineering Systems: A Lyapunov-Based Approach., Birkhäuser, Boston 2003. Zbl1060.93003
  20. Kim, C. Y., Song, D. Z., Xu, Y. L., Yi, J. G., Wu, X. Y., 10.1109/tro.2014.2333097, IEEE Trans. Rob. 30 (2014), 1161-1173. DOI10.1109/tro.2014.2333097
  21. Deng, Z., Hong, Y., 10.1142/s230138501640001x, Unmanned Systems 4 (2016), 5-13. DOI10.1142/s230138501640001x
  22. Spong, M., Hutchinson, S., Vidyasagar, M., 10.1108/ir.2006.33.5.403.1, John Wiley and Sons, Hoboken 2006. DOI10.1108/ir.2006.33.5.403.1
  23. Meng, Z., Yang, T., Shi, G., Dimarogonas, D. V., Hong, Y., Johansson, K. H., 10.1109/cdc.2014.7040462, In: IEEE 53rd Ann. Conf. Decision and Control (CDC), Los Angeles 2014, pp. 6830-6835. DOI10.1109/cdc.2014.7040462
  24. Rockafellar, R., 10.1017/s0013091500010142, Princeton University Press, Princeton 1970. Zbl1011.49013MR0274683DOI10.1017/s0013091500010142
  25. Godsil, C. D., Royle, G., 10.1007/978-1-4613-0163-9, Springer, New York 2001. Zbl0968.05002MR1829620DOI10.1007/978-1-4613-0163-9
  26. Zhu, W., Jiang, Z. P., 10.1109/tac.2014.2357131, IEEE Trans. Automat. Control 60 (2015), 1362-1367. MR3351418DOI10.1109/tac.2014.2357131

NotesEmbed ?

top

You must be logged in to post comments.