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Affiliation(s)

1. Faculty of Science and Technology, Department of Physics, University of Abou-bakr Belkaïd, B.P. 119, Tlemcen, Algeria 2. Materials and Renewable Energy Research Unit M.R.E.R.U., University of Abou-bakr Belkaïd, B.P. 119, Tlemcen, Algeria 3. Energy Laboratory in Drylands, University of Bechar, Bechar, Algeria 4. Euro-Mediterranean Institute of Environment and Renewable Energies, University of Valenciennes, France

ABSTRACT

The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system (MIMO ° such as the agricultural greenhouse.) First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.

KEYWORDS

Greenhouse, microclimate, modeling, fuzzy controller, optimization, solar energy, climate model, temperature

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References
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