Prognosis and Health Management methodologies require efficient parameter estimation approaches to enable systematic system reconfiguration and adaptive control to accommodate faulty behaviors, and to predict future system states. However, accurate and timely on-line parameter estimation of complex, nonlinear systems is difficult and can be computationally expensive. In this work, we propose a more efficient technique for on-line parameter estimation in TRANSCEND. This new approach is based on previous works on model decomposition and dependency compilation. We generate a set of smaller estimation tasks from the global estimation problem to reduce the computational burden. We tested the approach in a nonlinear three-tank system. Cur- rent results demonstrate that our method is more efficient and it does not compromise on the accuracy in the estimation.
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learning systems, model-based methods
T. Escobet, E. Gelso, M. Krysander, M. Nyberg, X. Olive, B. Pulido, and L. Trave ́-Massuye`s. Min- imal structurally overdetermined sets for residual generation: A comparison of alternative approaches. In Proceedings of the IFAC-Safeprocess 2009, Barcelona, Spain, 2009.
(Biswas et al., 2009) G. Biswas, X. Koutsoukos, A. Bregon, and B. Pulido. Analytic redundancy, possible conflicts, and TCG-based fault signature diagnosis applied to nonlinear dynamic systems. In Proceedings of the IFAC-Safeprocess 2009, Barcelona, Spain, 2009.
causal graphs. In Proceeding of the 23rd Euro-pean Conference on Modelling and Simulation, ECMS09, Madrid, Spain, 2009.
(Cordier et al., 2004) M.O. Cordier, P. Dague, F . L e ́ v y , J . M o n t m a i n , M . S t a r o s w i e c k i , a n d L. Trave ́-Massuye`s. Conflicts versus analytical redundancy relations: a comparative analysis of the model-based diagnosis approach from the artificial intelligence and automatic control perspectives. IEEE Trans. Syst. Man Cy. B., 34(5):2163–2177, 2004.
(Escobet and Trave ́-Massuye`s, 2001) T. Escobet and L. Trave ́-Massuye`s. Parameter estimation methods for fault detection and isolation. In Proceedings of the 12th International Workshop on Principles of Diagnosis (The BRIDGE Workshop), 2001.
(Gertler, 1998) J.J. Gertler. Fault detection and diagnosis in Engineering Systems. Marcel Dekker, Inc., Basel, 1998.
(Gertler, 2002) J.J. Gertler. All linear methods are equal - and extendible to (some) nonlinearities. International Journal of Robust and Nonlinear Control, pages 629–648, 2002.
(Isermann, 2006) R. Isermann. Fault-Diagnosis System. An Introduction from Fault Detection to Fault Tolerance. Springer, 2006.
(Kirk, 1999) R. E. Kirk. Statistics: An Introduction. Fort Worth: Harcourt Brace, 1999.
(Manders et al., 2000) E. J. Manders, S. Narasimhan, G. Biswas, and P. J. Mosterman. A combined qualitative/quantitative approach for fault isolation in continuous dynamic systems. In Proceedings of the 4th Symposium on Fault Detection, Supervision, and Safety for Technical Processes, pages 1074– 1079, 2000.
(Blanke et al., 2006) M. Blanke, J. Lunze, and M. Staroswiecki.
Fault Tolerant Control. Springer, 2006.
(Bregon et al., 2009) A. Bregon, B. Pulido, G. Biswas, and X. Koutsoukos. Generating possible conflicts from bond graphs using temporal
Armengol, A. Bregon,M. Kinnaert, Diagnosis and (Mosterman and Biswas, 1999) P. Mosterman and G. Biswas. Diagnosis of continuous valued systems in transient operating regions. IEEE Trans. Syst. Man Cy. A., 29(6):554–565, 1999.
(Patton et al., 2000) R. J. Patton, P. M. Frank, and R. N. Clark. Issues in fault diagnosis for dynamic systems. Springer Verlag, New York, 2000.
(Pouliezos and Stavrakakis, 1994) A.D. Pouliezos and G.S. Stavrakakis. Real time fault monitoring of industrial processes. Microprocessor-based systems engineering. Kluwer Academic Publishers, Dordrecht, 1994.
(Pulido and Alonso-Gonzalez, 2004) B. Pulido and C. Alonso-Gonzalez. Possible conflicts: a compilation technique for consistency-based diagnosis. IEEE Trans. Syst. Man Cy. B., 34(5):2192–2206, 2004.
(Reiter, 1987) R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57–95, 1987.
(Roychoudhury et al., 2009) I. Roychoudhury, G. Biswas, and X. Koutsoukos. Designing distributed diagnosers for complex continuous systems. IEEE Transactions on Automated Sciences and Engineering (T-ASE), 6, (to appear) 2009.
(Williams and Millar, 1998) B.C. Williams and B. Millar. Decompositional model-based learning and its analogy to diagnosis. In Proceedings of (AAAI-98), 1998.
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