Consensus-based state estimation for multi-agent systems with constraint information

Chen Hu; Weiwei Qin; Zhenhua Li; Bing He; Gang Liu

Kybernetika (2017)

  • Volume: 53, Issue: 3, page 545-561
  • ISSN: 0023-5954

Abstract

top
This paper considers a distributed state estimation problem for multi-agent systems under state inequality constraints. We first give a distributed estimation algorithm by projecting the consensus estimate with help of the consensus-based Kalman filter (CKF) and projection on the surface of constraints. The consensus step performs not only on the state estimation but also on the error covariance obtained by each agent. Under collective observability and connective assumptions, we show that consensus of error covariance is bounded. Based on the Lyapunov method and projection, we provide and prove convergence conditions of the proposed algorithm and demonstrate its effectiveness via numerical simulations.

How to cite

top

Hu, Chen, et al. "Consensus-based state estimation for multi-agent systems with constraint information." Kybernetika 53.3 (2017): 545-561. <http://eudml.org/doc/294636>.

@article{Hu2017,
abstract = {This paper considers a distributed state estimation problem for multi-agent systems under state inequality constraints. We first give a distributed estimation algorithm by projecting the consensus estimate with help of the consensus-based Kalman filter (CKF) and projection on the surface of constraints. The consensus step performs not only on the state estimation but also on the error covariance obtained by each agent. Under collective observability and connective assumptions, we show that consensus of error covariance is bounded. Based on the Lyapunov method and projection, we provide and prove convergence conditions of the proposed algorithm and demonstrate its effectiveness via numerical simulations.},
author = {Hu, Chen, Qin, Weiwei, Li, Zhenhua, He, Bing, Liu, Gang},
journal = {Kybernetika},
keywords = {multi-agent systems; distributed Kalman filter; state constraints; stability},
language = {eng},
number = {3},
pages = {545-561},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Consensus-based state estimation for multi-agent systems with constraint information},
url = {http://eudml.org/doc/294636},
volume = {53},
year = {2017},
}

TY - JOUR
AU - Hu, Chen
AU - Qin, Weiwei
AU - Li, Zhenhua
AU - He, Bing
AU - Liu, Gang
TI - Consensus-based state estimation for multi-agent systems with constraint information
JO - Kybernetika
PY - 2017
PB - Institute of Information Theory and Automation AS CR
VL - 53
IS - 3
SP - 545
EP - 561
AB - This paper considers a distributed state estimation problem for multi-agent systems under state inequality constraints. We first give a distributed estimation algorithm by projecting the consensus estimate with help of the consensus-based Kalman filter (CKF) and projection on the surface of constraints. The consensus step performs not only on the state estimation but also on the error covariance obtained by each agent. Under collective observability and connective assumptions, we show that consensus of error covariance is bounded. Based on the Lyapunov method and projection, we provide and prove convergence conditions of the proposed algorithm and demonstrate its effectiveness via numerical simulations.
LA - eng
KW - multi-agent systems; distributed Kalman filter; state constraints; stability
UR - http://eudml.org/doc/294636
ER -

References

top
  1. Agniel, R. G., Jury, E. I, 10.1137/0309027, SIAM J. Control 9 (1971), 372-384. MR0304038DOI10.1137/0309027
  2. Battistelli, G., Chisci, L., 10.1016/j.automatica.2013.11.042, Automatica 50 (2014), 707-718. MR3173970DOI10.1016/j.automatica.2013.11.042
  3. Bell, B. M., Burke, J. V., Pillonetto, G., 10.1016/j.automatica.2008.05.029, Automatica 45 (2009), 25-33. MR2531490DOI10.1016/j.automatica.2008.05.029
  4. Boyd, S., Vandenberghe, L., 10.1017/cbo9780511804441, Cambridge University Press, Cambridge 2004. Zbl1058.90049MR2061575DOI10.1017/cbo9780511804441
  5. Cattivelli, F., Sayed, A., 10.1109/tac.2010.2042987, IEEE Trans. Automat. Control 55 (2010), 2069-2084. MR2722500DOI10.1109/tac.2010.2042987
  6. Das, S., Moura, J. M. F., 10.1109/tsp.2015.2424205, IEEE Trans. Signal Process. 63 (2015), 4458-4473. MR3375283DOI10.1109/tsp.2015.2424205
  7. Godsil, C., Royle, G., 10.1007/978-1-4613-0163-9, Springer-Verlag, New York 2001. Zbl0968.05002MR1829620DOI10.1007/978-1-4613-0163-9
  8. Goodwin, G. C., Seron, M. M., Doná, J. A. De, 10.1007/b138145, Springer-Verlag, New York 2006. MR2085919DOI10.1007/b138145
  9. Gupta, N., Hauser, R., , arXiv preprint arXiv:0709.2791 MR0426293DOI
  10. Hu, J., Hu, X., 10.1109/chicc.2008.4605514, In: Proc. 27th Chinese Control Conference, Kunming 2008, 540-545. MR2425665DOI10.1109/chicc.2008.4605514
  11. Hu, J., Hu, X., 10.1016/j.automatica.2010.08.016, Automatica 46 (2010), 2041-2046. MR2878229DOI10.1016/j.automatica.2010.08.016
  12. Hu, C., Qin, W., He, B., Liu, G., 10.14736/kyb-2015-5-0814, Kybernetika 51 (2014), 814-829. MR3445986DOI10.14736/kyb-2015-5-0814
  13. Hu, J., Xie, L., Zhang, C., 10.1109/tsp.2011.2175386, IEEE Trans. Signal Process. 60 (2012), 891-902. MR2919485DOI10.1109/tsp.2011.2175386
  14. Kamal, A. T., Farrell, J. A., Roy-Chowdhury, A. K., 10.1109/tac.2013.2277621, IEEE Trans. Automat. Control 58 (2013), 3112-3125. MR3152272DOI10.1109/tac.2013.2277621
  15. Khan, U. A., Jadbabaie, A., 10.1016/j.automatica.2014.05.008, Automatica 50 (2014), 1909-1914. MR3230893DOI10.1016/j.automatica.2014.05.008
  16. Ko, S., Bitmead, R., 10.1016/j.automatica.2007.01.017, Automatica 43 (2007), 1363-1368. MR2320519DOI10.1016/j.automatica.2007.01.017
  17. Matei, I., Baras, J. S., 10.1016/j.automatica.2012.05.042, Automatica 48 (2012), 1776-1782. MR2950429DOI10.1016/j.automatica.2012.05.042
  18. Nedić, A., Ozdaglar, A., Parrilo, P. A., 10.1109/tac.2010.2041686, IEEE Trans. Automat Control 55 (2010), 922-938. MR2654432DOI10.1109/tac.2010.2041686
  19. Olfati-Saber, R., 10.1109/cdc.2007.4434303, in Proc. IEEE Conference on Decision and Control, New Orleans 2007, pp. 5492-5498. DOI10.1109/cdc.2007.4434303
  20. Olfati-Saber, R., 10.1109/cdc.2009.5399678, In: Proc. Joint IEEE Conference on Decision and Control and Chinese Control Conference, Shanghai 2009, pp. 7036-7042. DOI10.1109/cdc.2009.5399678
  21. Reif, K., Günther, S., Yaz, E., Unbehauen, R., 10.1109/9.754809, IEEE Trans. Automat. Control 44 (1999), 714-728. MR1684426DOI10.1109/9.754809
  22. Shi, G., Johansson, K., Hong, Y., 10.1109/tac.2012.2215261, IEEE Trans. Automatic Control 58 (2013), 610-622. MR3029459DOI10.1109/tac.2012.2215261
  23. Simon, D., 10.1049/iet-cta.2009.0032, IET Control Theory Appl. 4 (2010), 1303-1318. MR2757297DOI10.1049/iet-cta.2009.0032
  24. Simon, D., Chia, T. L., 10.1109/7.993234, IEEE Trans. Aerospace Electronic Systems 38 (2002), 128-136. DOI10.1109/7.993234
  25. Simon, D., Simon, D. L., 10.1049/ip-cta:20050074, IEE Proc. Control Theory Appl. 153 (2006), 371-378. DOI10.1049/ip-cta:20050074
  26. Stanković, S. S., Stanković, M. S., Stipanović, D. M., 10.1016/j.automatica.2009.02.014, Automatica 45 (2009), 1397-1406. MR2879441DOI10.1016/j.automatica.2009.02.014
  27. Tarn, T. J., Rasis, Y., 10.1109/tac.1976.1101300, IEEE Trans. Automat. Control 21 (1976), 441-448. MR0411794DOI10.1109/tac.1976.1101300
  28. Xiao, L., Boyd, S., 10.1016/j.sysconle.2004.02.022, Syst. Control Lett. 53 (2004), 65-78. Zbl1157.90347MR2077189DOI10.1016/j.sysconle.2004.02.022
  29. Zhou, Z., Fang, H., Hong, Y., 10.1109/icarcv.2012.6485124, In: Proc. 12th International Conference on Control Automation Robotics Vision (ICARCV), Guangzhou 2012, pp. 1818-1823. DOI10.1109/icarcv.2012.6485124
  30. Zhou, Z., Fang, H., Hong, Y., 10.1109/tac.2013.2246476, IEEE Trans. Automat. Control 58 (2013), 2096-2101. MR3090041DOI10.1109/tac.2013.2246476

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.