Greenhouse Air Temperature Control Using Fuzzy PD+I and Neuro-Fuzzy Hybrid System Controller


(*) Corresponding author


Authors' affiliations


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


This work describes the application of fuzzy logic control (FLC) and neuro-fuzzy hybrid system for temperature regulation in agricultural process. The treated greenhouse is considered a non- linear SISO process and subject to strong external disturbances. The inside outsides climate model of the environmental greenhouse, and the automatically collected data sets of Avignon, France are used to simulate and test the proposed method. The control objective is to maintain inside air temperature of an almost closed greenhouse at a specified set-point by manipulating the heating air flux.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords


Climate Model; Greenhouse; Temperature; FLC; Neuro-Fuzzy Hybrid System

Full Text:

PDF


References


Boulard, T., Draoui, B., Neirac, F., 1996. Calibration and validation of a greenhouse climate control model. Acta Hortic. (ISHS) 406, 49-62.
http://dx.doi.org/10.17660/actahortic.1996.406.4

Draoui.B. Caractérisation et analyse du bilan thermo hydrique d’une serre horticole. Identification in situ des paramètres d’un modèle dynamique. Thèse de doctorat de l’université de Nice Sophia Antipolis, 1994

Bounaama.F, Modélisation neuronale et polynomiale d'une serre horticole et commande par réseau neuronale et logique floue.

Mémoire de Magister en physique énergétique du Centre Universitaire de Bechar(08000) Algerie 2001.

Jantzen, Jan, Tuning of Fuzzy PID Controller, (Technical report no. 98-H 871, Technical U. of Denmark, Denmark, September 1998).

Yen, John, and Reza Langari, Fuzzy Logic: Intelligence, Control, and Information (Prentice-Hall, Inc., 1999).
http://dx.doi.org/10.1016/b978-012443870-5.50010-1

Gadoura, I., K. Zenger, T. Suntio, P. Vallittu. New Methodology for Design, Analysis, and Validation of DC/DC Converters Based on Advanced Controllers. Proc. of the 1999 IEEE International Telecommunications Energy Conference. Copenhagen, Denmark. pp.23-1.
http://dx.doi.org/10.1109/intlec.1999.794111

Adaptive Fuzzy Systems and control: Design and Stability Analysis. (Upper Saddle River, NJ: Prentice-Hall, 1994).
http://dx.doi.org/10.1002/aic.690471222

L.X Wang and J.M. Mendel, Fuzzy basis functions, universal approximation, and orthogonal least squares learning, IEEE Trans. Neural Networks, vol.3, pp.807- 814, Oct. 1992.

Jacek M. Zurada. Introduction to Artificial Neural Systems. West Info Acess, Singar-pore, 1992).

Li-Xin Wang. Adaptive Fuzzy Systems and Control. (Prentice Hall, Englewood Cli_s, New Jersey, 1994).

X. Blasco et al., Model-based predictive control of greenhouse climate for reducing energy and water consumption, Comput. Electron. Agric. (2006).
http://dx.doi.org/10.1016/j.compag.2006.12.001


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize