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Title: Distributed $H_{\infty }$ estimation for moving target under switching multi-agent network (English)
Author: Chen, Hu
Author: Weiwei, Qin
Author: Bing, He
Author: Gang, Liu
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 51
Issue: 5
Year: 2015
Pages: 814-829
Summary lang: English
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Category: math
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Summary: In this paper, the distributed $H_\infty$ estimation problem is investigated for a moving target with local communication and switching topology. Based on the solution of the algebraic Riccati equation, a recursive algorithm is proposed using constant gain. The stability of the proposed algorithm is analysed by using the Lyapounov method, and a lower bound for estimation errors is obtained for the proposed common $H_\infty$ filter. Moreover, a bound for the $H_{\infty}$ parameter is obtained by means of the solution of the algebraic Riccati equation. Finally, a simulation example is employed to illustrate the effectiveness of the proposed estimation algorithm. (English)
Keyword: multi-agent systems
Keyword: distributed estimation
Keyword: $H_\infty $ filter
Keyword: switching topology
MSC: 62A10
MSC: 93E12
idZBL: Zbl 06537782
idMR: MR3445986
DOI: 10.14736/kyb-2015-5-0814
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Date available: 2015-12-16T19:03:11Z
Last updated: 2018-01-10
Stable URL: http://hdl.handle.net/10338.dmlcz/144745
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Reference: [1] Cattivelli, F. S., Sayed, A. H.: Diffusion LMS strategies for distributed estimation..IEEE Trans. Signal Process. 58 (2010), 1035-1048. MR 2751419, 10.1109/tsp.2009.2033729
Reference: [2] Cattivelli, F. S., Sayed, A. H.: Diffusion strategies for distributed Kalman filtering and smoothing..IEEE Trans. Automat. Control 55 (2010), 2069-2084. MR 2722500, 10.1109/tac.2010.2042987
Reference: [3] Dong, H., Wang, Z., Gao, H.: Distributed $H_\infty$ filtering for a class of Markovian jump nonlinear time-delay systems over Lossy sensor networks..IEEE Trans. Industr. Electronics 60 (2013), pp. 4665-4672. 10.1109/tie.2012.2213553
Reference: [4] Godsil, C., Royle, G.: Algebraic Graph Theory..Springer-Verlag, New York 2001. Zbl 0968.05002, MR 1829620
Reference: [5] Hong, Y., Hu, J., Gao, L. X.: Tracking control for multi-agent consensus with an active leader and variable topology..Automatica 42 (2006), 1177-1182. Zbl 1117.93300, MR 2230987, 10.1016/j.automatica.2006.02.013
Reference: [6] Hong, Y., Wang, X.: Multi-agent tracking of a high-dementional active leader with switching topology..J. Systems Sci. Complex. 22 (2009), 722-731. MR 2565265, 10.1007/s11424-009-9197-z
Reference: [7] Horn, R. A., Johnson, C. R.: Matrix Analysis..Cambridge University Press, 2012. Zbl 0801.15001
Reference: [8] Hu, J., Xie, L., Zhang, C.: Diffusion Kalman filtering based on covariance intersection..In: Proc. 18th IFAC World Congress, Milano 2011, pp. 12471-12476. MR 2919485, 10.1007/s11424-009-9197-z
Reference: [9] Kailath, T., Sayed, A. H., Hassibi, B.: Linear Estimation..Prentice Hall, New Jersey 2000. Zbl 0862.93056
Reference: [10] Kar, S., Moura, J. M. F.: Grossip and distributed Kalman filtering: weak consensus under weak detectability..IEEE Trans. Signal Process. 59 (2011), 1766-1784. MR 2807748, 10.1109/tsp.2010.2100385
Reference: [11] Marshall, A. W., Olkin, I., Arnold, B. C.: Inequalities: Theory of Majorization and Its Applications..Springer-Verlag, New York 2010. Zbl 1219.26003, MR 2759813
Reference: [12] Nelson, T. R., Freeman, R. A.: Decentralized $H_\infty$ filtering in a multi-agent system..In: Proc. 2009 American Control Conference, St. Louis 2009, pp. 5755-5760. 10.1109/acc.2009.5160702
Reference: [13] Nemirovskii, A., Gahinet, P.: The projective method for solving linear matrix inequalities..In: Proc. 1994 American Control Conference, Baltimore 1994, pp. 840-844. 10.1109/acc.1994.751861
Reference: [14] Olfati-Saber, R.: Distributed Kalman filtering for sensor networks..In: Proc. 46th IEEE Conference on Decision and Control, New Orleans 2007, pp. 5492-5498. 10.1109/cdc.2007.4434303
Reference: [15] Olfati-Saber, R.: Kalman-consensus filter : optimality, stability, and performance..In: Proc. 48th IEEE Conference on Decision and Control, Proc. 28th Chinese Control Conference, Shanghai 2009, pp. 7036-7042. 10.1109/cdc.2009.5399678
Reference: [16] Olfati-Saber, R., Jalalkamali, P.: Collaborative target tracking using distributed Kalman filtering on mobile sensor networks..In: Proc. 2011 American Control Conference, San Francisco 2011, pp. 1100-1105. 10.1109/acc.2011.5990979
Reference: [17] Ramamurthy, H., Prabhu, B. S., Gadh, R., Madni, A. M.: Wireless industrial monitoring and control using a smart sensor platform..IEEE Sensors J. 7 (2007), 611-618. 10.1109/jsen.2007.894135
Reference: [18] Saboori, I., Khorasani, K.: $H_\infty$ consensus achievement of multi-agent systems with disrected and switching topology networks..IEEE Trans. Automat. Control 59 (2014), 3104-3109. MR 3271167, 10.1109/tac.2014.2358071
Reference: [19] Shen, B., Wang, Z., Hung, Y. S.: Distributed $H_\infty$-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case..Automatica 46 (2010), 1682-1688. Zbl 1204.93122, MR 2877323, 10.1016/j.automatica.2010.06.025
Reference: [20] Ugrinovskii, V.: Distributed robust filtering with $H_\infty$ consensus of estimates..Automatica 47 (2011), 1-13. Zbl 1209.93152, MR 2878241, 10.1016/j.automatica.2010.10.002
Reference: [21] Ugrinovskii, V., Fridman, E.: A Round-Robin type protocol for distributed estimation with $H_\infty$ consensus..Systems Control Lett. 69 (2014), 103-110. Zbl 1288.93009, MR 3212828, 10.1016/j.sysconle.2014.05.001
Reference: [22] Zhang, Q., Zhang, J.: Distributed parameter estimation over unreliable networks with Markovian switching topologies..IEEE Trans. Automat. Control 57 (2012), 2545-2560. MR 2991656, 10.1109/tac.2012.2188353
Reference: [23] Zhou, Z., Fang, H., Hong, Y.: Distributed estimation for moving target under switching interconnection network..In: Proc. 12th International Conference on Control Automation Robotics Vision (ICARCV), Guangzhou 2012, pp. 1818-1823. 10.1109/icarcv.2012.6485302
Reference: [24] Zhou, Z., Fang, H., Hong, Y.: Distributed estimation for moving target based on state-consensus strategy..IEEE Trans. Automat. Control 58 (2013), 2096-2101. MR 3090041, 10.1109/tac.2013.2246476
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