Approximate Modelling by means of Orthonormal Functions
1991 (English)In: Modeling, Estimation and Control of Systems with Uncertainty: Proceedings of a Conference held in Sopron, Hungary, September, 1990 / [ed] Giovanni B. Di Masi, Andrea Gombani, Alexander B. Kurzhansky, Boston: Birkhäuser Verlag, 1991, 449-467 p.Chapter in book (Refereed)
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
Boston: Birkhäuser Verlag, 1991. 449-467 p.
, Progress in Systems and Control Theory, 10
Laguerre filter, Kautz filter, Approximation, Complex system, Linear regression, Least square method, Control theory Congresses, Stochastic processes Congresses
IdentifiersURN: urn:nbn:se:liu:diva-91637DOI: 10.1007/978-1-4612-0443-5_31ISBN: 0-8176-3580-7 (alk. paper)ISBN: 3-7643-3580-7 (alk. paper)OAI: oai:DiVA.org:liu-91637DiVA: diva2:626047
1990 IIASA Symposium on Modeling and Control of Systems with Uncertainty, Sopron, Hungary, September, 1990