Robust identification of non-linear greenhouse model using evolutionary algorithms
This paper presents the non-linear modelling, based on first principle equations, for a climatic model of a greenhouse and the estimation of the feasible parameter set ( FPS) when the identification error is bounded simultaneously by several norms. The robust identification problem is transformed in...
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| Veröffentlicht in: | Control engineering practice Jg. 16; H. 5; S. 515 - 530 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Oxford
Elsevier Ltd
01.05.2008
Elsevier |
| Schlagworte: | |
| ISSN: | 0967-0661, 1873-6939 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This paper presents the non-linear modelling, based on first principle equations, for a climatic model of a greenhouse and the estimation of the feasible parameter set (
FPS) when the identification error is bounded simultaneously by several norms. The robust identification problem is transformed into a multimodal optimization problem with an infinite number of global minima that constitute the
FPS. For the optimization task, a special evolutionary algorithm (
ε
-GA) is presented, which characterizes the
FPS by means of a discrete set of models that are well distributed along the
FPS. A procedure for determining the norm bounds, such that
FPS
≠
∅
, is presented. |
|---|---|
| ISSN: | 0967-0661 1873-6939 |
| DOI: | 10.1016/j.conengprac.2007.06.001 |