Fischer, Martin ; Schmidt, Martin ; Kavsek-Biasizzo, Katarina (1997)
Nonlinear predictive control based on the extraction of step-response models from Takagi-Sugeno fuzzy systems.
American Control Conference (ACC) 1997. Albuquerque, USA (06.06.1997-06.06.1997)
doi: 10.1109/ACC.1997.611983
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
This paper deals with nonlinear predictive control based on higher order Takagi-Sugeno fuzzy systems which can also be interpreted as generalized radial basis function networks. We investigate how the fuzzy models can be linked to a special type of model based predictive control algorithm, namely the dynamic matrix control (DMC). Previously, purely linear step response models were used for long-range prediction. Here, the method is extended to nonlinear processes. Therefore, various step responses for different operating points are extracted from the fuzzy model. For performance evaluation, a heat exchanger is identified by means of the local linear model tree algorithm and controlled by the modified DMC.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 1997 |
| Autor(en): | Fischer, Martin ; Schmidt, Martin ; Kavsek-Biasizzo, Katarina |
| Art des Eintrags: | Bibliographie |
| Titel: | Nonlinear predictive control based on the extraction of step-response models from Takagi-Sugeno fuzzy systems |
| Sprache: | Englisch |
| Publikationsjahr: | 1997 |
| Verlag: | IEEE |
| Buchtitel: | Proceedings of the 1997 American Control Conference |
| Veranstaltungstitel: | American Control Conference (ACC) 1997 |
| Veranstaltungsort: | Albuquerque, USA |
| Veranstaltungsdatum: | 06.06.1997-06.06.1997 |
| DOI: | 10.1109/ACC.1997.611983 |
| Kurzbeschreibung (Abstract): | This paper deals with nonlinear predictive control based on higher order Takagi-Sugeno fuzzy systems which can also be interpreted as generalized radial basis function networks. We investigate how the fuzzy models can be linked to a special type of model based predictive control algorithm, namely the dynamic matrix control (DMC). Previously, purely linear step response models were used for long-range prediction. Here, the method is extended to nonlinear processes. Therefore, various step responses for different operating points are extracted from the fuzzy model. For performance evaluation, a heat exchanger is identified by means of the local linear model tree algorithm and controlled by the modified DMC. |
| Zusätzliche Informationen: | Vol. 5 |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik |
| Hinterlegungsdatum: | 19 Nov 2008 16:27 |
| Letzte Änderung: | 01 Jun 2023 12:34 |
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