- Autor(i):
- J. Števek – A. Szűcs – M. Kvasnica – M. Fikar – Š. Kozák
- Názov:
- Two steps piecewise affine identification of nonlinear systems
- Časopis:
- Archives of Control Sciences
- Rok:
- 2012
- Zväzok:
- 22
- Číslo:
- 4
- Strany:
- 371–388
- Jazyk:
- angličtina
- Anotácia:
- Given a set of input-output measurements, the paper proposes a method for approximation of a nonlinear system by a piecewise affine model (PWA). First step of the two-stage procedure is identification from input-output data, in order to obtain an appropriate nonlinear function in analytic form. The analytic expression of the model can be represented either by a static nonlinear function or by a dynamic system and can be obtained using a basis function expansion modeling approach. Subsequently we employ nonlinear programming to derive optimal PWA approximation of the identified model such that the approximation error is minimized. Moreover, we show that approximation of multivariate systems can be transformed into a series of one-dimensional approximations, which can be solved efficiently using standard optimization techniques.
- ISSN:
- 1230-2384
- Kategória publikácie:
- ADE – Vedecké práce v ostatných zahraničných časopisoch
- Oddelenie:
- OIaRP
- Vložil/Upravil:
- Ing. Juraj Števek, PhD.
- Posledná úprava:
- 8.1.2013 13:41:46
- Plný text:
- Plný text nie je prístupný verejnosti, ale môžete požiadať o kópiu niektorého z autorov
- Príloha:
- 1365.rar (36.28 kB)
- BibTeX:
- @article{uiam1365,
author = {J. {\v{S}}tevek and A. Sz\~ucs and M. Kvasnica and M. Fikar and {\v{S}}. Koz\'ak}, title = {Two steps piecewise affine identification of nonlinear systems}, journal = {Archives of Control Sciences}, year = {2012}, volume = {22}, number = {4}, pages = {371-388}, annote = {Given a set of input-output measurements, the paper proposes a method for approximation of a nonlinear system by a piecewise affine model (PWA). First step of the two-stage procedure is identification from input-output data, in order to obtain an appropriate nonlinear function in analytic form. The analytic expression of the model can be represented either by a static nonlinear function or by a dynamic system and can be obtained using a basis function expansion modeling approach. Subsequently we employ nonlinear programming to derive optimal PWA approximation of the identified model such that the approximation error is minimized. Moreover, we show that approximation of multivariate systems can be transformed into a series of one-dimensional approximations, which can be solved efficiently using standard optimization techniques.}, url = {https://www.uiam.sk/assets/publication_info.php?id_pub=1365}