Kybernetika 53 no. 1, 179-194, 2017

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

Xue-Fang Wang, Zhenhua Deng, Song Ma and Xian DuDOI: 10.14736/kyb-2017-1-0179

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.

Keywords:

event-triggered control, multi-agent system, optimal consensus, Euler-Lagrangian system

Classification:

34K35, 34H05, 49K35, 65K10, 90C25

References:

  1. A. Nedic and A. Ozdaglar: Distributed subgradient methods for multi-agent optimization. IEEE Trans. Automat. Control 54 (2009), 48-61.   DOI:10.1109/tac.2008.2009515
  2. G. Shi, K. H. Johansson and Y. Hong: Reaching an optimal consensus: dynamical systems that compute intersections of convex sets. IEEE Trans. Automat. Control 58 (2013), 610-622.   DOI:10.1109/tac.2012.2215261
  3. S. Bose, S. H. Low, T. Teeraratkul and B. Hassibi: Equivalent relaxations of optimal power flow. IEEE Trans. Automat. Control 60 (2015), 729-742.   DOI:10.1109/tac.2014.2357112
  4. Y. Zhang, Y. Lou, Y. Hong. and L. Xie: Distributed projection-based algorithms for source localization in wireless sensor networks. IEEE Trans. Wireless Commun. 14 (2015), 3131-3142.   DOI:10.1109/twc.2015.2402672
  5. Q. Liu and J. Wang: A second-order multi-agent network for bound-constrained distributed optimization. IEEE Trans. Automat. Control 60 (2015), 3310-3315.   DOI:10.1109/tac.2015.2416927
  6. P. Yi, Y. Hong and F. Liu: Distributed gradient algorithm for constrained optimization with application to load sharing in power systems. Systems Control Lett. 83 (2015), 45-52.   DOI:10.1016/j.sysconle.2015.06.006
  7. X. Wang, P. Yi and Y. Hong: Dynamical optimization for multi-agent systems with external disturbance. Control Theory Technol. 12 (2014), 132-138.   DOI:10.1007/s11768-014-0036-y
  8. X. Wang, Y. Hong and H. Ji: Distributed optimization for a class of nonlinear multiagent systems With disturbance rejection. IEEE Trans. Cybernet. 46 (2016), 1655-1666.   DOI:10.1109/tcyb.2015.2453167
  9. Y. Zhang, Z. Deng and Y. Hong: Distributed optimal coordination for multiple heterogenous Euler-Lagrangian systems. Automatica 79 (2017), 207-213.   DOI:10.1016/j.automatica.2017.01.004
  10. P. Yi and Y. Hong: Stochastic sub-gradient algoirthm for distributed optimization with random sleep scheme. Control Theory Technol. 13 (2015), 333-347.   DOI:10.1007/s11768-015-5100-8
  11. J. Hu, G. Chen and H. Li: Distributed event-triggered tracking control of leader-follower multi-agent systems with communication delays. Kybernetika 47 (2011), 630-643.   CrossRef
  12. Z. Deng and Y. Hong: Distributed event-triggered optimization for multi-agent systems with disturbance rejection. In: 12th IEEE Int. Conf. Control and Autom., Kathmandu 2016, pp 13-18.   DOI:10.1109/icca.2016.7505245
  13. P. Tabuada: Event-triggered real-time scheduling of stabilizing control tasks. IEEE Trans. Automat. Control 52 (2007), 1680-1685.   DOI:10.1109/tac.2007.904277
  14. W. S. Chen and W. Ren: Event-triggered zero-gradient-sum distributed consensus optimization over directed networks. Automatica 65 (2016), 90-97.   DOI:10.1016/j.automatica.2015.11.015
  15. Z. Deng, X. Wang and Y. Hong: Distributed optimization design with triggers for disturbed continuous-time multi-agent systems. IET Control Theory Appl. 11 (2017), 2, 282-290.   DOI:10.1049/iet-cta.2016.0795
  16. S. S. Kia, J. Cortes and S. Martinez: Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication. Automatica 55 (2015), 254-264.   DOI:10.1016/j.automatica.2015.03.001
  17. H. Cai and J. Huang: Leader-following consensus of multiple uncertain Euler-Lagrange systems under switching network topology. Int. J. Gene. Sys., 43 (2014), 294-304.   DOI:10.1080/03081079.2014.883714
  18. S. J. Chung and J. J. E. Slotine: Cooperative robot control and concurrent synchronization of lagrangian systems. IEEE Trans. Robotics 25 (2009), 686-700.   DOI:10.1109/tro.2009.2014125
  19. W. E. Dixon: Nonlinear Control of Engineering Systems: A Lyapunov-Based Approach. Birkhäuser, Boston 2003.   CrossRef
  20. C. Y. Kim, D. Z. Song, Y. L. Xu, J. G. Yi and X. Y. Wu: Cooperative search of multiple unknown transient radio sources using multiple paired mobile robots. IEEE Trans. Rob. 30 (2014), 1161-1173.   DOI:10.1109/tro.2014.2333097
  21. Z. Deng and Y. Hong: Multi-agent optimization design for autonomous lagrangian systems. Unmanned Systems 4 (2016), 5-13.   DOI:10.1142/s230138501640001x
  22. M. Spong, S. Hutchinson and M. Vidyasagar: Robot Modeling and Control. John Wiley and Sons, Hoboken 2006.   DOI:10.1108/ir.2006.33.5.403.1
  23. Z. Meng, T. Yang, G. Shi, D. V. Dimarogonas, Y. Hong and K. H. Johansson: Set target aggregation of multiple mechanical systems. In: IEEE 53rd Ann. Conf. Decision and Control (CDC), Los Angeles 2014, pp. 6830-6835.   DOI:10.1109/cdc.2014.7040462
  24. R. Rockafellar: Convex Analysis. Princeton University Press, Princeton 1970.   DOI:10.1017/s0013091500010142
  25. C. D. Godsil and G. Royle: Algebraic Graph Theory. Springer, New York 2001.   DOI:10.1007/978-1-4613-0163-9
  26. W. Zhu and Z. P. Jiang: Event-based leader-following consensus of multi-agent systems with input time delay. IEEE Trans. Automat. Control 60 (2015), 1362-1367.   DOI:10.1109/tac.2014.2357131