Algorithm for selection of best orthonormal rational basis
1997 (English)In: Proceedings of the IEEE Conference on Decision and Control, San Diego, CA, USA, 1997, Vol. 2, no Piscataway, NJ, United States, 1277-1282 p.Conference paper (Refereed)
This contribution deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parameterized by a pre-specified set of poles. Given this structure and experimental data a model can be estimated using linear regression techniques. Since the variance of the estimated model increases with the number of estimated parameters, the objective is to find structures that are as compact/parsimonious as possible. A natural approach would be to estimate the poles, but this leads to nonlinear optimization with possible local minima. In this paper, a best basis algorithm is derived for the generalized orthonormal rational bases. Combined with linear regression and thresholding this leads to compact transfer function representations.
Place, publisher, year, edition, pages
San Diego, CA, USA, 1997. Vol. 2, no Piscataway, NJ, United States, 1277-1282 p.
, Proceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5)
Algorithms, Control system synthesis, Mathematical models, Regression analysis, Transfer functions, Orthonormal generalized basis, Parameter estimation
IdentifiersURN: urn:nbn:se:kth:diva-55415OAI: oai:DiVA.org:kth-55415DiVA: diva2:471613
Sponsors: IEEE NR 201408052012-01-022012-01-022013-09-05Bibliographically approved