Asymptotic variance expressions for closed-loop identification

Abstract

Asymptotic variance expressions are analyzed for models that are identified on the basis of closed-loop data. The considered methods comprise the classical 'direct' method. as well as the more recently developed indirect methods, employing coprime factorized models, dual Youla/Kucera parametrizations and the two-stage approach. The variance expressions are compared with the open-loop ituation, and evaluated in terms of their relevance for subsequent model-based control design. (C) 2001 Elsevier Science Ltd. All rights reserved.