M. Bayoudh, L. Travé-massuyes, and X. Olive, Active Diagnosis of Hybrid Systems Guided by Diagnosability Properties, IFAC Proceedings Volumes, vol.42, issue.8, p.14981503, 2009.
DOI : 10.3182/20090630-4-ES-2003.00244

L. Blackmore and B. Williams, Finite Horizon Control Design for Optimal Discrimination between Several Models, Proceedings of the 45th IEEE Conference on Decision and Control, p.11471152, 2006.
DOI : 10.1109/CDC.2006.377045

E. Chanthery, Y. Pencole, and N. Bussac, An AO*-like algorithm implementation for active diagnosis, Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2010.

D. Eriksson, E. Frisk, and M. Krysander, A method for quantitative fault diagnosability analysis of stochastic linear descriptor models, Automatica, vol.49, issue.6, pp.49-15911600, 2013.
DOI : 10.1016/j.automatica.2013.02.045

M. Gholami, H. Schioler, and T. Bak, Active fault diagnosis for hybrid systems based on sensitivity analysis and EKF, Proceedings of the 2011 American Control Conference, p.244249, 2011.
DOI : 10.1109/ACC.2011.5991038

K. R. Pattipati and M. G. Alexandridis, Application of heuristic search and information theory to sequential fault diagnosis. Systems, Man and Cybernetics, IEEE Transactions, vol.20, issue.4, p.872887, 1990.

R. Pons, A. Subias, and L. Travé-massuyès, Iterative hybrid causal model based diagnosis: Application to automotive embedded functions, Engineering Applications of Artificial Intelligence, vol.37, p.319335, 2015.
DOI : 10.1016/j.engappai.2014.09.016

URL : https://hal.archives-ouvertes.fr/hal-01400360

&. ?imandl and . Pun?ochá?, Active fault detection and control: Unified formulation and optimal design, Automatica, vol.45, issue.9, 2009.
DOI : 10.1016/j.automatica.2009.04.028

, SAFEPROCESS 2015