In this paper, we propose an external model based, data-driven approach to robust output regulation. No a priori knowledge of the plant and the exosystem is required, apart from their state dimension and an upper bound on the exosystem frequencies. The core of the method lies in an error-feedback reset logic for the state of the external model.
De Carolis, G., Galeani, S., Sassano, M. (2017). Data driven, robust output regulation via external models. In Control and Automation (MED), 2017 25th Mediterranean Conference on (pp.1263-1268). IEEE [10.1109/MED.2017.7984291].
Data driven, robust output regulation via external models
De Carolis G.;Galeani S.;Sassano M.
2017-01-01
Abstract
In this paper, we propose an external model based, data-driven approach to robust output regulation. No a priori knowledge of the plant and the exosystem is required, apart from their state dimension and an upper bound on the exosystem frequencies. The core of the method lies in an error-feedback reset logic for the state of the external model.File in questo prodotto:
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