Soft computing for greenhouse climate control
The methodology proposed in the paper applies artificial intelligence (AI) techniques to the modeling and control of some climate variables within a greenhouse. The nonlinear physical phenomena governing the dynamics of temperature and humidity in such systems are, in fact, difficult to model and co...
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| Veröffentlicht in: | IEEE transactions on fuzzy systems 2000-12, Vol.8 (6), p.753-760 |
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| container_end_page | 760 |
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| container_issue | 6 |
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| container_title | IEEE transactions on fuzzy systems |
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| creator | Caponetto, R. Fortuna, L. Nunnari, G. Occhipinti, L. Xibilia, M.G. |
| description | The methodology proposed in the paper applies artificial intelligence (AI) techniques to the modeling and control of some climate variables within a greenhouse. The nonlinear physical phenomena governing the dynamics of temperature and humidity in such systems are, in fact, difficult to model and control using traditional techniques. The paper proposes a framework for the development of soft computing-based controllers in modern greenhouses. |
| doi_str_mv | 10.1109/91.890333 |
| format | Article |
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| ispartof | IEEE transactions on fuzzy systems, 2000-12, Vol.8 (6), p.753-760 |
| issn | 1063-6706 1941-0034 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_27717093 |
| source | IEEE Electronic Library (IEL) |
| subjects | Artificial intelligence Control systems Expert systems Fuzzy logic Humidity control Nonlinear control systems PD control Plants (biology) Proportional control Temperature control |
| title | Soft computing for greenhouse climate control |
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