Robust estimation for discrete time-varying systems with limited communication capacity
In this paper, we consider the state estimation problem for linear discrete time‐varying systems subject to limited communication capacity which includes measurement quantization, random transmission delay and data‐packet dropouts. Based on transforming the three communication limitations into the s...
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| Published in | Asian journal of control Vol. 14; no. 2; pp. 502 - 511 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
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Chichester, UK
John Wiley & Sons, Ltd
01.03.2012
Wiley Subscription Services, Inc |
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| Abstract | In this paper, we consider the state estimation problem for linear discrete time‐varying systems subject to limited communication capacity which includes measurement quantization, random transmission delay and data‐packet dropouts. Based on transforming the three communication limitations into the system with norm‐bounded uncertainties and stochastic matrices, we design a robust filter such that, for all the communication limitations, the error state of the filtering process is mean square bounded. An upper bound on the variance of the state estimation error is first found, and then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati‐like difference equations which also provide a recursive algorithm suitable for online computation. A simulation example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.
Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society |
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| AbstractList | In this paper, we consider the state estimation problem for linear discrete time-varying systems subject to limited communication capacity which includes measurement quantization, random transmission delay and data-packet dropouts. Based on transforming the three communication limitations into the system with norm-bounded uncertainties and stochastic matrices, we design a robust filter such that, for all the communication limitations, the error state of the filtering process is mean square bounded. An upper bound on the variance of the state estimation error is first found, and then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations which also provide a recursive algorithm suitable for online computation. A simulation example is presented to demonstrate the effectiveness and applicability of the proposed algorithm. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [PUBLICATION ABSTRACT] In this paper, we consider the state estimation problem for linear discrete time‐varying systems subject to limited communication capacity which includes measurement quantization, random transmission delay and data‐packet dropouts. Based on transforming the three communication limitations into the system with norm‐bounded uncertainties and stochastic matrices, we design a robust filter such that, for all the communication limitations, the error state of the filtering process is mean square bounded. An upper bound on the variance of the state estimation error is first found, and then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati‐like difference equations which also provide a recursive algorithm suitable for online computation. A simulation example is presented to demonstrate the effectiveness and applicability of the proposed algorithm. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society |
| Author | Guo, Ge Wang, Bao-Feng |
| Author_xml | – sequence: 1 givenname: Bao-Feng surname: Wang fullname: Wang, Bao-Feng email: wbfdm@163.com organization: Information Engineering Institute, Dalian University, Dalian 116622, China – sequence: 2 givenname: Ge surname: Guo fullname: Guo, Ge email: geguo@yeah.net organization: School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China |
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| Cites_doi | 10.1016/j.automatica.2007.09.016 10.1109/TAC.2007.902766 10.1016/j.sigpro.2009.02.002 10.1109/CDC.2006.377700 10.1109/TAC.2002.800668 10.1109/TAC.2005.858689 10.1109/78.942638 10.1109/TSP.2003.816861 10.1111/j.1934-6093.2003.tb00128.x 10.1109/LSP.2005.847890 10.1016/j.automatica.2006.10.023 10.1109/59.962439 10.1109/TCSI.2008.918009 10.1016/j.automatica.2008.11.009 10.1002/asjc.213 10.1002/rnc.749 10.1016/j.automatica.2008.10.028 10.1109/TAC.2003.820140 10.1016/j.automatica.2007.09.023 10.1109/TAC.2003.814272 10.1080/00207170701196968 10.1109/TAC.2007.908316 10.1016/S0005-1098(01)00298-9 10.1109/LSP.2006.873148 10.1002/asjc.201 10.1016/S0005-1098(03)00117-1 10.1109/TSP.2004.827188 10.1109/TCSII.2004.829572 |
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| Notes | istex:1B8006F5C27990C77490A85F73389879A97CD824 ArticleID:ASJC300 This work is supported by National Natural Science Foun-dation of China under grant number 60504017, Fok Ying Tong Education Foundation under grant 111066 and Program for New Century Excellent Talents in University under grant NCET-04-0982. ark:/67375/WNG-VQV13LL1-T This work is supported by National Natural Science Foun‐dation of China under grant number 60504017, Fok Ying Tong Education Foundation under grant 111066 and Program for New Century Excellent Talents in University under grant NCET‐04‐0982. ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 |
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| References_xml | – reference: Anderson,B. D. O. and J. B.Moore, Optimal Filtering, Prentice-Hall, Englewood Cliffs, N.J. (1979). – reference: Dong, Z., and Z.You, "Finite-Horizon Robust Kalman filtering for uncertain discrete time-varying systems with uncertain-covariance white noises," IEEE Signal Process. Lett., Vol. 13, No. 8, pp. 493-496 (2006). – reference: Smith, S. C., and P.Seiler, "Estimation with lossy measurements: jump estimators for jump systems," IEEE Trans. Autom. Control, Vol. 48, No. 12, pp. 2163-2171 (2003). – reference: Hung, Y. S. and F.Yang, "Robust H∞ filtering with error variance constraints for uncertain discrete time-varying systems with uncertainty," Automatica, Vol. 39, No. 7, pp. 1185-1194 (2003). – reference: Fridman, E., U.Shaked, and L.Xie, "Robust H2 filtering of linear systems with time delays," Int. J. Robust Nonlinear Control, Vol. 13, pp. 983-1010 (2003). – reference: Wang, F., and V.Balakrishnan, "Robust steady-state filtering for systems with deterministic and stochastic uncertainties," IEEE Trans. Sign. Process., Vol. 51, No. 10, pp. 2550-2558 (2003). – reference: Wei, G. L., Z. D.Wang, and H. S.Shu, "Robust filtering with stochastic nonlinearities and multiple missing measurements," Automatica, Vol. 45, No. 3, pp. 836-841 (2009). – reference: Graham, C. G., I. S.Eduardo, and E. Q.Daniel, "Analysis and design of networked control systems using the additive noise model methodology," Asian J. Control, Vol. 12, No. 4, pp. 443-459 (2010). – reference: Fu, M., and L.Xie, "The sector bound approach to quantized feedback control," IEEE Trans. Autom. Control, Vol. 50, No. 11, pp. 1698-1711 (2005). – reference: Wang, Z. D., F. W.Yang, and W. C.Daniel, "Robust finite-horizon filtering for stochastic system with missing measurements," IEEE Signal Process. Lett., Vol. 12, No. 6, pp. 437-440 (2005). – reference: Huang, M. Y., and S.Dey, "Stability of Kalman filtering with Markovian packet losses," Automatica, Vol. 43, No. 4, pp. 598-607 (2007). – reference: Wang, Z. D., Y. R.Liu, and X. H.Liu, "H∞ filtering for uncertain stochastic time-delay systems with sector-bound nonlinearities," Automatica, Vol. 44, No. 5, pp. 1268-1277 (2008). – reference: Zhu, X., Y. C.Soh, and L.Xie, "Design and analysis of discrete-time robust Kalman filters," Automatica, Vol. 38, No. 6, pp. 1069-1077 (2002). – reference: Su, C. L., and C. N.Lu, "Interconnected network state estimation using randomly delayed measurements," IEEE Trans. Power Systems, Vol. 16, No. 4, pp. 870-878 (2001). – reference: Fang, X. S., and J. C.Wang, "Sampled-data H∞ control for networked systems with random packet dropouts," Asian J. Control, Vol. 12, No. 4, pp. 549-557 (2010). – reference: Xu, S. Y., and T. W.Chen, "Robust H∞ filtering for uncertain stochastic time-delay systems," Asian J. Control, Vol. 5, No. 3, pp. 364-373 (2003). – reference: Gao, H. J., and T. W.Chen, "H∞ Estimation for uncertain systems with limited communication capacity," IEEE Trans. Autom. Control, Vol. 52, No. 11, pp. 2070-2084 (2007). – reference: Yang, F. W., Z. D.Wang, and G.Feng et al., "Robust filtering with randomly varying sensor delay: the finite-horizon case," IEEE Trans. Circuits Syst. Regul. Pap., Vol. 56, No. 3, pp. 664-672 (2009). – reference: Sahebsara, M., T. W.Chen, and S. L.Shah, "Optimal H2 filtering in networked control systems with multiple packet dropouts," IEEE Trans. Autom. Control, Vol. 52, No. 8, pp. 1508-1513 (2007). – reference: He, X., Z. D.Wang, and D.Zhou, "Robust H∞ filtering for networked systems with multiple state delays," Int. J. Control, Vol. 80, No. 8, pp. 1217-1232 (2007). – reference: Wang, Z. D., W. C.Daniel, and X. H.Liu, "Robust filtering under randomly varying sensor delay with variance constraints," IEEE Trans. Circuits Syst. II-Express Briefs, Vol. 51, No. 6, pp. 320-326 (2004). – reference: Sun, S. L., "Linear minimum variance estimators for systems with bounded random measurement delays and packet dropouts," Signal Process., Vol. 89, pp. 1457-1466 (2009). – reference: Fu, M., C. E.de Souza, and Z.Luo, "Finite horizon robust Kalman filter design," IEEE Trans. Signal Process., Vol. 49, No. 9, pp. 2103-2112 (2001). – reference: Wang, Z. D., W. C.Ho, and X. H.Liu, "Variance-constrained filtering for uncertain stochastic systems with missing measurements," IEEE Trans. Autom. Control, Vol. 48, No. 7, pp. 1254-1258 (2003). – reference: Sun, S. L., L. H.Xie, and W. D.Xiao, "Optimal linear estimation for systems with multiple packet dropouts," Automatica, Vol. 44, pp. 1333-1342 (2008). – reference: Yang, F. W., Z. D.Wang, and Y. S.Hung, "Robust Kalman filtering for discrete time-varying uncertain systems with multiplication noises," IEEE Trans. Autom. Control, Vol. 47, No. 7, pp. 1179-1183 (2002). – reference: Shen, B., Z. D.Wang, and H. S.Shu, et al. "H∞ filtering for nonlinear discrete-time stochastic systems with randomly varying sensor delays," Automatica, Vol. 45, No. 4, pp. 1032-1037 (2009). – reference: Gao, H. J., and C. H.Wang, "A delay-dependent approach to robust H∞ filtering for uncertain discrete-time state-delayed systems," IEEE Trans. Signal Process., Vol. 52, No. 6, pp. 1631-1640 (2004). – volume: 13 start-page: 493 issue: 8 year: 2006 end-page: 496 article-title: Finite‐Horizon Robust Kalman filtering for uncertain discrete time‐varying systems with uncertain‐covariance white noises publication-title: IEEE Signal Process. 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| Snippet | In this paper, we consider the state estimation problem for linear discrete time‐varying systems subject to limited communication capacity which includes... In this paper, we consider the state estimation problem for linear discrete time-varying systems subject to limited communication capacity which includes... |
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| SubjectTerms | Measurement quantization networked control systems packets dropouts robust estimation time delay |
| Title | Robust estimation for discrete time-varying systems with limited communication capacity |
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