Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design
2009 (English)In: Automatica, ISSN 0005-1098, Vol. 45, no 3, 623-633 p.Article in journal (Refereed) Published
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.
Experiment design, LMI-s, Binary inputs, Stochastic regression, Adaptive control, stochastic regression-models, recursive estimators, dynamic-systems, respect
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-18291DOI: 10.1016/j.automatica.2008.09.01ISI: 000264576400003ScopusID: 2-s2.0-60449106306OAI: oai:DiVA.org:kth-18291DiVA: diva2:336337
FunderSwedish Research Council, 621-2002-4514Swedish Research Council, 621-2005-4345
QC 201507242010-08-052010-08-052015-07-24Bibliographically approved