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Introduction to interval estimation and interval estimation design
During this seminar, basic interval analysis tools for the identification of nonlinear systems are presented. The main assumption is that the measurement noise is assumed to be bounded without any additional knowledge. In such a case, we do not look for an optimal single estimation but a set of all the feasible values is characterized. This approach is very useful in several applications such as fault detection. Interval observers design based on the theory of positive systems is also introduced. It is shown that under some mild conditions it is possible to design two classical observers in order to estimate all the values of the state vector wich are consistent with the measurements and with the model. This robust estimation can be useful to compute dynamic thresholds for fault detection and also for model predictive control and robust control.
Tarek Raissi received the Engineering degree from National Engineers School of Tunis in 2000, the Master in Automatic Control from Central School of Lille in 2001, the Ph.D. degree from the University of Paris XII in 2004 and the Accreditation to Supervise/Conduct Research (HDR) from the University of Bordeaux in 2012. From 2005 to 2011 he was an Associate Professor at the University of Bordeaux. Currently, he is a Full Professor at the Conservatoire National des Arts et Metiers, Paris. He is a member of the IFAC Technical Committee “Modelling, Identification and Signal Processing” and a Senior member of IEEE. His research interests include fault detection and isolation, nonlinear systems estimation and robust control.