H∞-norm estimation is usually an important aspect of robust control design. The aim of this paper is to develop a data-driven estimation method exploiting iterative input design, without requiring parametric modeling. More specifically, the estimation problem is formulated as a sequential game, whose solution is derived within the prediction with expert advice framework. The proposed method is shown to be competitive with the state-of-the-art techniques.

Data-driven H∞-norm estimation via expert advice

Rallo, Gianmarco;Formentin, Simone;Savaresi, Sergio M.
2017-01-01

Abstract

H∞-norm estimation is usually an important aspect of robust control design. The aim of this paper is to develop a data-driven estimation method exploiting iterative input design, without requiring parametric modeling. More specifically, the estimation problem is formulated as a sequential game, whose solution is derived within the prediction with expert advice framework. The proposed method is shown to be competitive with the state-of-the-art techniques.
2017
Proc of IEEE 56th Annual Conference on Decision and Control, CDC 2017
9781509028733
Decision Sciences (miscellaneous); Industrial and Manufacturing Engineering; Control and Optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1063535
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