Data-Driven Superstabilizing Control Under Quadratically-Bounded Errors-in-Variables Noise
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DOI: 10.1109/lcsys.2024.3410888
Abstract: The Errors-in-Variables model of system identification/control involves nontrivial input and measurement corruption of observed data, resulting in generically nonconvex optimization problems. This letter performs full-state-feedback stabilizing control of all discrete-time linear systems that are consistent… read more here.
Keywords: superstabilizing control; control; driven superstabilizing; errors variables ... See more keywords