In Marconi et al. 2007, it was shown that a solution to the output regulation problem for minimum-phase normal forms always exists. That approach, however, yields only an existence result, and no general analytic procedure is known to actually choose the regulator’s degrees of freedom, even for simple problems. In this paper we propose an adaptive regulator that, leveraging the aforementioned existence result, self-tunes online according to an optimization policy. To this aim, the regulator may employ every system identification scheme that fulfills some given strong stability properties, and the asymptotic regulation error is proved to be directly related to the prediction capabilities of the identifier.

Adaptive output regulation via nonlinear Luenberger observers

Bin M.
Writing – Original Draft Preparation
;
Bernard P.
Writing – Original Draft Preparation
;
Marconi L.
Writing – Review & Editing
2019

Abstract

In Marconi et al. 2007, it was shown that a solution to the output regulation problem for minimum-phase normal forms always exists. That approach, however, yields only an existence result, and no general analytic procedure is known to actually choose the regulator’s degrees of freedom, even for simple problems. In this paper we propose an adaptive regulator that, leveraging the aforementioned existence result, self-tunes online according to an optimization policy. To this aim, the regulator may employ every system identification scheme that fulfills some given strong stability properties, and the asymptotic regulation error is proved to be directly related to the prediction capabilities of the identifier.
2019
11th IFAC Symposium on Nonlinear Control Systems NOLCOS 2019
580
585
Bin M.; Bernard P.; Marconi L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/715241
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