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Approximate Modelling by Means of Orthonormal Functions
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1990 (English)Report (Other academic)
Abstract [en]

ARX, AR and FIR modeling are generalized by repacing the delay operator by discrete Laguerre/Kautz filters. The aim is to obtain useful low order approximate models of complex systems by using a priori information about the dominating time constants of the system. An important characteristic of these models are that they can be written in a linear regressions form. Hence, the least squares methods can be applied for system identification. By deriving naturally associated state-space realizations of Laguerre/Kautz models, we obtain model representations that are more directly suitable for control design etc. The orthonormal property of Laguerre/Kautz functions is very important, since it guarantees a Toeplitz structure of the corresponding least squares normal equations. This property enables us to determine persistence of excitation conditions and analyze asymp totic statistical properties of Laguerre/Kautz model estimates.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1990.
Series
LiTH-ISY-I, ISSN 8765-4321 ; 1138
Keyword [en]
Laguerre filter, Kautz filter, Approximation, Complex system, Linear regression, Least square method
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55323OAI: oai:DiVA.org:liu-55323DiVA: diva2:316060
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2013-07-28

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