@. Belkherchi, A. Belmehdi, and B. Dahhou, «Structural analysis of multiple faults isolability in fermentation bioprocess» XVI International Conference on Systems Science, Septembre, pp.4-6, 2007.

@. Belkherchi, A. Belmehdi, and B. Dahhou, «L'approche structurelle pour la détection et l'isolation de fautes dans un procédé de traitement des eaux usées» Conférence Internationale Francophone d'Automatique, Bucarest (Roumanie), 2008.

@. Blanke and R. I. , Fault-tolerant control systems ??? A holistic view, Control Engineering Practice, vol.5, issue.5, pp.693-702, 1997.
DOI : 10.1016/S0967-0661(97)00051-8

@. Blanke and T. Lorentzen, SATOOL - A SOFTWARE TOOL FOR STRUCTURAL ANALYSIS OF COMPLEX AUTOMATION SYSTEMS 1,2, 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, 2006.
DOI : 10.3182/20060829-4-CN-2909.00104

@. P. Cassar, M. Staroswiecki, and P. Declerck, CARTON « Langages formels -Calculabilité et complexité», vuibert«Structural Decomposition of Large Scale Systems for the Design of Failure Detection and Isolation Procedures», ? Journal of Systems Science, vol.20, issue.1, pp.31-42, 1994.

@. P. Cassar, M. Staroswiecki, and V. Cocquempot, «Optimal residual design for model-based fault detection and isolation», 3rd European Control Conference ECC AAZ95, 1995.

@. P. Bibliographie, M. Cassar, and . Staroswiecki, «A structural approach for the design of failure detection and identification systems», IFAC, IFIP, IMACS Conference on control of industrial systems, pp.329-334, 1997.

@. Cassar, M. Starswiecki, and V. Cocquempot, «optimal design of FDI systems via parity space and observer based approaches», p.91, 1999.

@. Chittaro and R. Ranon, Hierarchical model-based diagnosis based on structural abstraction, Artificial Intelligence, vol.155, issue.1-2, pp.147-182, 2004.
DOI : 10.1016/j.artint.2003.06.003

@. Jerome-cieslak and «. , Analyse et synthèse d'une architecture coopérative pour la commande tolérante aux défauts», 2007.

@. O. Cole and P. S. Keogh, Towards fault-tolerant active control of rotor???magnetic bearing systems, Control Engineering Practice, vol.12, issue.4, 2003.
DOI : 10.1016/S0967-0661(03)00173-4

@. Commault, J. Dion, O. Sename, and A. R. , MOTYEIAN «Observer-Based Fault Detection and Isolation for Structured Systems», IEEE transactions on automatic control, vol.47, issue.12, 2002.

M. Staroswiecki and L. Travé-massuyés, «AI and automatic control approaches of model-based diagnosis: links and underlying», SAFEPROCESS'2000 Conference, 2000.

M. Staroswiecki and L. Travé-massuyés, «Conflicts versus analytical redundancy relations, a comparative analysis of the model-based diagnosis approach from the artificial intelligence and automatic control perspectives», IEEE Transactions on Systems, Man, and Cybernetics, pp.2163-2177, 2004.

@. De-kleer and B. Williams, Diagnosing multiple faults, Artificial Intelligence, vol.32, issue.1, pp.97-130, 1987.
DOI : 10.1016/0004-3702(87)90063-4

@. Dimitrova, E. Gadjeva, and A. , Van den Bossche and V.Valchev, «A modelbased approach to automatic diagnosis using general purpose circuit simulators», IEEE ISIE 2006, pp.2972-2977, 2007.

D. Dustegor, M. Staroswiecki, and V. Cocquempot, «Structural analysis for residual generation: toward implementation» proceedings of the, ?, pp.2-4, 2004.

D. Dustegor, M. Staroswiecki, and V. Cocquempot, «Structural Analysis for Residual generation: Implementation issues considerations, ? ». conference on Control, 2004.

@. Dustegor, E. Frisk, V. Cocquempot, M. Krysander, and M. Staroswiecki, «Structural analysis of fault isolability in the DAMADICS benchmark», Control Engineering Practice, pp.597-608, 2006.

@. Gao and P. Antsaklis, Reconfigurable control system design via perfect model following, International Journal of Control, vol.56, issue.4, pp.783-798, 1992.
DOI : 10.1109/NAECON.1989.40230

@. R. Gelso, S. M. Castillo, and J. Armengol, «Structural analysis and consistency techniques for robust modelbased fault diagnosis», 2008.

@. Bibliographie, K. R. Gopinathan, C. J. Mehra, and . Runkle, « Model predictive faulttolerant temperature control scheme for hot isostatic pressing furnaces, American Control Conference, pp.637-641, 1999.

@. Y. Huang and R. F. Stengel, « Restructurable control using proportional-integral implicite model-following», Journal of Guidance, Control, and Dynamics, vol.13, issue.6, pp.303-309, 1990.

@. Isermann and P. Ballé-«, Trends in the application of model-based fault detection and diagnosis of technical processes, Control Engineering Practice, vol.5, issue.5, pp.709-719, 1997.
DOI : 10.1016/S0967-0661(97)00053-1

@. Jorgensen, R. I. Zamanabadi, and M. , KRISTENSEN «Prototype software for automated structural analysis of systems», Proceedings of the IFAC 10th Symposium -Large Scale Systems: Theory and Applications, pp.523-529, 2004.

@. Karpenko and N. Sepehri, Fault-tolerant control of a servohydraulic positioning system with crossport leakage, IEEE Transactions on Control Systems Technology, vol.13, issue.1, pp.155-161, 2005.
DOI : 10.1109/TCST.2004.838570

M. Krysander and M. Nyberg, «Structural Analysis utilizing MSS Sets with Application to a Paper Plant, Proc. of the Thirteenth International Workshop on Principles of Diagnosis, 2002.

@. Krysander, J. Aslund, and M. Nyberg, An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.38, issue.1, pp.197-206, 2008.
DOI : 10.1109/TSMCA.2007.909555

@. Li, N. Kabbaj, B. Dahhou, J. Aguilar, and . Martin, «Fault-tolerant control for nonlinear dynamic systems», IFAC Symposium on Power Plants & Power Systems control, pp.15-19, 2003.

@. Marx, D. Koenig, and D. Georges-«robust, Robust Fault-Tolerant Control for Descriptor Systems, IEEE Transactions on Automatic Control, vol.49, issue.10, pp.1869-1876, 2004.
DOI : 10.1109/TAC.2004.835595

URL : https://hal.archives-ouvertes.fr/hal-00152242

@. D. Morse and K. A. Ossman, Model following reconfigurable flight control system for the AFTI/F-16, Journal of Guidance, Control, and Dynamics, vol.13, issue.6, pp.969-976, 1990.
DOI : 10.2514/3.20568

@. Bibliographie, Nyberg and M.Krysander, «Combining AI, FDI, and statistical hypothesistesting in a framework for diagnosis», 2003.

@. J. Patton, Fault detection and diagnosis in aerospace systems using analytical redundancy, Computing & Control Engineering Journal, vol.2, issue.3, pp.127-136, 1991.
DOI : 10.1049/cce:19910031

@. J. Patton, «Robustness issues in fault-tolerant control», Fault Diagnosis and Control System Reconfiguration, IEE Colloquium, pp.1-125, 1993.

@. Ploix, S. Touaf, and J. Flaus, «A logical framework for isolation in fault diagnosis», SAFEPROCESS'2003conference, 2003.

@. Pulido and C. Alonso, Possible Conflicts: A Compilation Technique for Consistency-Based Diagnosis, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.34, issue.5, pp.1083-4419, 2004.
DOI : 10.1109/TSMCB.2004.835007

@. Reiter, A theory of diagnosis from first principles, Artificial Intelligence, vol.32, issue.1, pp.57-95, 1987.
DOI : 10.1016/0004-3702(87)90062-2

@. Svärd and M. Nyberg-«, Residual Generators for Fault Diagnosis Using Computation Sequences With Mixed Causality Applied to Automotive Systems, IEEE Transactions on Systems, Man, and Cybernetics --Part A: Systems and Humans, pp.401310-1328, 2010.
DOI : 10.1109/TSMCA.2010.2049993

@. Sorsa, H. N. Koivo, and H. Koivisto, «Neural networks in process fault diagnosis», Systems, Man and Cybernetics, IEEE Transactions on, vol.21, issue.4, pp.815-825, 1991.

@. Staroswiecki and A. L. , From control to supervision, Annual Reviews in Control, vol.25, pp.1-11, 2001.
DOI : 10.1016/S1367-5788(01)00002-5

@. Bibliographie, STAROSWIECKI, «Fault diagnosis and fault tolerant control, chapter Structural analysis for fault detection and isolation and for fault tolerant control», Encyclopedia of Lif Support Systems, 2002.

@. Trave-massuyes, T. Escobet, and R. Milne, «Model-based diagnosability and sensor placement application to a frame 6 gas turbine subsystem», International joint Conference on Artificial intelligence IJCAI'01, pp.551-556, 2001.

@. Trave-massuyes, T. Escobet, and S. Spanache, Diagnosability Analysis Based on Component-Supported Analytical Redundancy Relations, SAFEPROCESS'2003 Conference, 2003.
DOI : 10.1109/TSMCA.2006.878984

@. Trave-massuyes, T. Escobet, and X. Olive, «Diagnosability analysis based oncomponent supported analytical redundancy relations», IEEE Transactions, pp.1146-1160, 2006.
DOI : 10.1109/tsmca.2006.878984

@. Willsky, A survey of design methods for failure detection in dynamic systems, Automatica, vol.12, issue.6
DOI : 10.1016/0005-1098(76)90041-8

@. Yassine, S. Ploix, and J. Flaus, «New results for sensor placement with diagnosability purpose», 18th International Workshop on Principles of Diagnosis, p.7, 2007.

@. Yen and L. W. Ho, Fault tolerant control: an intelligent sliding mode control strategy, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), pp.4204-4208, 2000.
DOI : 10.1109/ACC.2000.877013

@. Yen and L. W. Ho, Online multiple-model-based fault diagnosis and accommodation, IEEE Transactions on Industrial Electronics, vol.50, issue.2, pp.296-312, 2003.
DOI : 10.1109/TIE.2003.809390

@. L. , T. K. Chang, and D. W. Yu, Fault Tolerant Control of Multivariable Processes Using Auto-Tuning PID Controller, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.35, issue.1, pp.32-43, 2005.
DOI : 10.1109/TSMCB.2004.839247

@. Izadi-zamanabadi and M. Staroswiecki, «A Structural Analysis Method Formulation for Fault-tolerant, Control System Design» Proceedings of the 39 th IEEE Conference on Decision and Control Sydney, 2000.

S. Fonction, recherche de touts les ensembles MSO possibles (M) 2. Pour chaque équation E dans M faire 3. Trouver les ensembles MSOs dans (M \ {E}), et les mettre dans SMSO; 4. Fin Étape 1.2: Trouver les OSM possibles 1

=. Si-variables, Si possible MSO est minime dans SMSO alors 4. Retirez tout-ensemble de MSO possibles dans SMSO; insérer MSO possibles dans SMSO 5. Fin 6. Si non 7. Pour chaque équation E' ? M faire 8. Pour chaque y ? (E'. inconnues ? variables) faire 9, Trouver possible MSO (M \ (E'), MSO possible? {E'}, variables ?{E'. inconnues} \ {y}

=. Mso and \. {e-'}, couplage causal valide pour le MSO, s'il est conforme, pour chaque équation dans MSO. 1. Fonction trouver cm possible (MSO, cm possible, SCM) 2. si MSO = = ? alors 3. Insérez cm possible en SMC; 4. Fin 5. pour chaque équation dans E' MSO faire 6. pour chaque interprétation causale C' dans E' faire 7. si (c', cm possible) consistent alors 8, Etape 2.2. cm possible est un