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Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design
Computer and Automation Institute of the Hungarian Academy of Sciences, (MTA SZTAKI),.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3672-5316
2009 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 45, no 3, 623-633 p.Article in journal (Refereed) Published
Abstract [en]

A key problem in optimal input design is that the solution depends on system parameters to be identified. In this contribution we provide formal results for convergence and asymptotic optimality of an adaptive input design method based on the certainty equivalence principle, i.e. for each time step an optimal input design problem is solved exactly using the present parameter estimate and one sample of this input is applied to the system. The results apply to stable ARX systems with the input restricted to be generated by white noise filtered through a finite impulse response filter, or a binary signal obtained from the latter by a static nonlinearity.

Place, publisher, year, edition, pages
2009. Vol. 45, no 3, 623-633 p.
Keyword [en]
Experiment design, LMI-s, Binary inputs, Stochastic regression, Adaptive control, stochastic regression-models, recursive estimators, dynamic-systems, respect
National Category
Control Engineering
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-18291ISI: 000264576400003Scopus ID: 2-s2.0-60449106306OAI: oai:DiVA.org:kth-18291DiVA: diva2:336337
Funder
Swedish Research Council, 621-2002-4514Swedish Research Council, 621-2005-4345
Note

QC 20150724

Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2017-06-02Bibliographically approved

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Hjalmarsson, HåkanMårtensson, Jonas

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