Asymptotic statistical analysis for model-based control design strategies

Title: Asymptotic statistical analysis for model-based control design strategies
Creator: Esparza, Alicia; Agüero, Juan C.; Rojas, Cristian R.; Godoy, Boris I.
Relation: Automatica Vol. 47, Issue 5, p. 1041-1046
Publisher Link: http://dx.doi.org/10.1016/j.automatica.2011.01.058
Publisher: Elsevier
Resource Type: journal article
Date: 2011
Description: In this paper, we generalize existing fundamental limitations on the accuracy of the estimation of dynamic models. In addition, we study the large sample statistical behavior of different estimation-based controller design strategies. In particular, fundamental limitations on the closed-loop performance using a controller obtained by Virtual Reference Feedback Tuning (VRFT) are studied. We also extend our results to more general estimation-based control design strategies. We present numerical examples to show the application of our results.
Subject: system identification; maximum likelihood; model-based control
Identifier: http://hdl.handle.net/1959.13/937114
Identifier: uon:12500
Identifier: ISSN:0005-1098
Language: eng
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