Integrating Subspace Identification and Prediction Error Methods
Subspace identification methods are attractive to identify MIMO linear systems via convex optimization problem and linear algebra decompositions. On the other hand, prediction error methods for this class of systems generally yield non-convex optimization problems. However in the latter case, available structure on the unknown model can be integrated in the identification problem. The core of the presentation is to present a new methodology (indicated by COSMOS) to integrate both worlds in a difference-of-convex optimization problem.
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Teacher / speaker
Michel Verhaegen
Michel Verhaegen received an engineering degree in aeronautics from the Delft University of Technology, The Netherlands, in 1982, and the doctoral degree in applied sciences from the Catholic University Leuven, Belgium, in 1985. From 1985 to 1994 he has been a research fellow of the U.S. National Research Council (NRC) and the Dutch Academy of Arts and Sciences. In the period 1994-1999 he was an Associate Professor of the control laboratory of the Delft University of Technology and became a full professor at the faculty of Applied Physics of the University of Twente in the Netherlands in 1999. From 2001 on he moved back to the University of Delft and joined the Delft Center for Systems and Control. His main research directions include system identification, distributed and fault tolerant control and data driven controller design methodologies. Application areas include control for high resolution imaging and wind energy. In 2014 he was a recipient of an advanced ERC grant.
AI for Time Series
Several research groups in the Flanders AI Research Program conduct world-class research on time series, both in the development of algorithms and tools, as in a wide area of application fields. In a recent poll in the Flanders AI community, ‘time series’ came up as the most wanted topic for future workshops or courses. With this seminar series, we bring together researchers that are interested in, or are conducting research related to, time series. We offer a varied program of national and international speakers.
Klik on the separate webinars below to (re)watch the recordings.
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