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2013 | 23 | 1 | 131-144
Tytuł artykułu

Mode set focused hybrid estimation

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Estimating the state of a hybrid system means accounting for the mode of operation or failure and the current state of the continuously valued entities concurrently. Existing hybrid estimation schemes try to overcome the problem of an exponentially growing number of possible mode-sequence/continuous-state combinations by merging hypotheses and/or deducing likelihood measures to identify tractable sets of the most likely hypotheses. However, they still suffer from unnecessarily high computational costs as the number of possible modes increases. Hybrid diagnosis schemes, on the other hand, estimate the current mode of operation/failure only, thus leaving the continuous evolution of the system implicit. This paper proposes a novel scheme that uses a combination of both the approaches in order to define posterior transition probabilities between the specified modes of the hybrid system, hence focusing better on relevant hypotheses. In order to demonstrate the effectiveness of the proposed method, the algorithm is applied to a satellite attitude control system and compared with existing hybrid estimation/diagnosis schemes, such as the Interacting Multiple Model (IMM) algorithm, a purely parity based method (HyDiag), and an existing hybrid Mode Estimation (hME) algorithm.
Rocznik
Tom
23
Numer
1
Strony
131-144
Opis fizyczny
Daty
wydano
2013
otrzymano
2011-11-14
poprawiono
2012-05-10
Twórcy
  • Institute of Electrical and Biomedical Engineering, UMIT, Eduard-Wallnöfer-Zentrum 1, 6060 Hall in Tyrol, Austria
  • Doctoral School of Information and Communications Engineering (ICE), Graz University of Technology, Rechbauerstrasse 12, 8010 Graz, Austria
  • Institute of Automation and Control Engineering, UMIT, Eduard-Wallnöfer-Zentrum 1, 6060 Hall in Tyrol, Austria
  • LAAS, CNRS, University of Toulouse, 7 Avenue du Colonel Roche, F-31400 Toulouse, France
  • LAAS, CNRS, University of Toulouse, 7 Avenue du Colonel Roche, F-31400 Toulouse, France
Bibliografia
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  • Bayoudh, M., Travé-Massuyès, L. and Olive, X. (2008). Hybrid systems diagnosis by coupling continuous and discrete event techniques, Proceedings of the IFAC World Congress, Seoul, Korea, pp. 7265-7270.
  • Benazera, E. and Travé-Massuyès, L. (2009). Set-theoretic estimation of hybrid system configurations, IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics 39(5): 1277-1291.
  • Benazera, E., Travé-Massuyès, L. and Dague, P. (2002). State tracking of uncertain hybrid concurrent systems, Proceedings of the 13th International Workshop on Principles of Diagnosis (DX02), Semmering, Austria, pp. 106-114.
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  • Cocquempot, V., El Mezyani, T. and Staroswiecki, M. (2004). Fault detection and isolation for hybrid systems using structured parity residuals, 5th Asian Control Conference, Melbourne, Australia, Vol. 2, pp. 1204-1212.
  • Daigle, M., Roychoudhury, I., Biswas, G., Koutsoukos, X., Patterson-Hine, A. and Poll, S. (2010). A comprehensive diagnosis methodology for complex hybrid systems: A case study on spacecraft power distribution systems, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 4(5): 917-931.
  • de Freitas, N. (2002). Rao-Blackwellised particle filtering for fault diagnosis, Proceedings of the IEEE Aerospace Conference 2002, Big Sky, MT, USA, Vol. 4, pp. 1767-1772.
  • Dearden, R. and Clancy, D. (2002). Particle filters for real-time fault detection in planetary rovers, 13th International Workshop on Principles of Diagnosis, DX02, Semmering, Austria, pp. 1-6.
  • Georges, J.-P., Theilliol, D., Cocquempot, V., Ponsart, J.-C. and Aubrun, C. (2011). Fault tolerance in networked control systems under intermittent observations, International Journal of Applied Mathematics and Computer Science 21(4): 639-648, DOI: 10.2478/v10006-011-0050-x.
  • Gertler, J. (1991). A survey of analytical redundancy methods in failure detection and isolation, Preprints of the IFAC SAFEPROCESS Symposium, Baden-Baden, Germany, pp. 9-21.
  • Henzinger, T. (1996). The theory of hybrid automata, Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science (LICS '96), New Brunswick, NJ, USA, pp. 278-292.
  • Hofbaur, M., Travé-Massuyès, L., Rienmüller, T. and Bayoudh, M. (2010). Overcoming non-discernibility through mode-sequence analytic redundancy relations in hybrid diagnosis and estimation, 21st International Workshop on Principles of Diagnosis DX-10, Portland, OR, USA, pp. 71-78.
  • Hofbaur, M.W. (2005). Hybrid Estimation of Complex Systems, Lectures Notes in Control and Information Sciences, Vol. 319, Springer-Verlag, Berlin/Heidelberg/New York, NY.
  • Hofbaur, M.W. and Williams, B.C. (2002). Mode estimation of probabilistic hybrid systems, in C. Tomlin and M. Greenstreet (Eds.), Hybrid Systems: Computation and Control, HSCC 2002, Lecture Notes in Computer Science, Vol. 2289, Springer-Verlag, Berlin/Heidelberg, pp. 253-266.
  • Hofbaur, M.W. and Williams, B.C. (2004). Hybrid estimation of complex systems, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34(5): 2178-2191.
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  • Koutsoukos, X., Kurien, J. and Zhao, F. (2002). Monitoring and diagnosis of hybrid systems using particle filtering methods, 15th International Symposium on Mathematical Theory Networks and Systems, South Bend, IN, USA pp. 1-15.
  • Li, X. and Bar-Shalom, Y. (1996). Multiple-model estimation with variable structure, IEEE Transactions on Automatic Control 41(4): 478-493.
  • Narasimhan, S. and Biswas, G. (2002). An approach to model-based diagnosis of hybrid systems, in C. Tomlin and M. Greenstreet (Eds.), Hybrid Systems: Computation and Control, HSCC 2002, Lecture Notes in Computer Science, Vol. 2289, Springer-Verlag, Berlin/Heidelberg, pp. 308-322.
  • Narasimhan, S., Dearden, R. and Benazera, E. (2004). Combining particle filters and consistency based approaches for monitoring and diagnosis of stochastic hybrid systems, Proceedings of the 15th International Workshop on Principles of Diagnosis (DX04), Carcassonne, France, pp. 123-128.
  • Olive, X. (2012). FDI(R) for satellites: How to deal with high availability and robustness in the space domain?, International Journal of Applied Mathematics and Computer Science 22(1): 99-107, DOI: 10.2478/v10006-012-0007-8.
  • Rienmüller, T., Bayoudh, M., Hofbaur, M. and Travé-Massuyès, L. (2009). Hybrid estimation through synergic mode-set focusing, IFAC SAFEPROCESS Symposium, Barcelona, Spain, pp. 462-467.
  • Semerdjiev, E. and Mihaylova, L. (1998). Adaptive interacting multiple model algorithm for manoeuvring ship tracking, 1998 International Conference on Information Fusion, Las Vegas, NV, USA, pp. 974-979.
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Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv23z1p131bwm
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