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SUMMARY:Talk of Prof. Ali Belabbas
DESCRIPTION:Prof. Ali Belabbas\nElectrical and Computer Engineering Department\nUniversity of Illinois, USA \nFriday 2017-07-21 14:00\n IKTD-Seminar-Room 1.264 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen \nAbstract \nLinear systems with process and observation noises are widely used in engineering and\nphysics to model systems as varied as the stock market and epidemics. Consider the estimation of\nthe state of such systems from the noisy measurements; the Kalman filter is known to be\nthe minimum mean square error estimator when the noises are Gaussian. We address here how to design\nthe sensors that minimize the error afforded by the Kalman filter. This problem of optimal sensor\ndesign, which is almost as old as the Kalman filter itself, is however not convex. As a\nconsequence, many ad hoc methods have been used over the years to solve it. We show in this talk\nhow a geometric approach allows us to characterize and obtain the optimal designs exactly. This\noptimal design yields the lowest possible estimation error from linear measurements with a fixed\nsignal to noise ratio. The approach can be used to solve the dual problem of optimal actuator\ndesign to minimize control energy. \n \n \nBiographical Information \nM.-A. Belabbas obtained his PhD degree in applied mathematics from Harvard University\nand his undergraduate degree from Ecole Centrale Paris and University de Louvain. He is currently\nan assistant professor in the Electrical and Computer Engineering department at the University of\nIllinois, Urbana-Champaign and the Coordinated Science Laboratory. His research interests are in\nnetworked control, geometric control and stochastic systems. He was a recipient of the 2014\nNSF Career Award.\n \n\n
DTSTART;VALUE=DATE:20170721
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/events/Talk-of-Prof.-Ali-Belabbas/
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