Brief paper: Asymptotic statistical analysis for model-based control design strategies

Authors:
Alicia Esparza;Juan C. Agüero;Cristian R. Rojas;Boris I. Godoy
Affiliations:
Department of Systems Engineering and Control, Universidad Politécnica de Valencia. Camino de Vera, s/n, 46022 Valencia, Spain;Centre for Complex Dynamic Systems and Control (CDSC), The University of Newcastle, NSW 2308, Australia;ACCESS Linnaeus Center, Electrical Engineering, KTH-Royal Institute of Technology, SE-100 44 Stockholm, Sweden;Centre for Complex Dynamic Systems and Control (CDSC), The University of Newcastle, NSW 2308, Australia
Venue:
Automatica (Journal of IFAC)
Year:
2011

Citing 8
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Abstract

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.