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Hankel structured low rank matrix completion

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If you have a question about this talk, please contact Dr Ioannis Lestas.

Hankel structured low rank matrices appear frequently in systems and control problems. Well known examples are model reduction and system identification (which correspond to Hankel structured low rank approximation). In this talk, we show that classical analysis and synthesis problems, such as simulation, prediction, input estimation, and output tracking are special cases of a Hankel structured low rank matrix completion problem. There is no computational advantage in solving the special problems as a general matrix completion problem, however, the many-to-one mapping has aesthetic appeal and reveals hidden relations.

This talk is part of the CUED Control Group Seminars series.

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