THE OPTIMAL MANAGEMENT OF THE MICRO CLIMATE OF THE AGRICULTURAL GREENHOUSE THROUGH THE MODELING OF..

Climate has a significant impact on plant physiological activities. Photosynthesis and temperature are primarily affected by radiation, which has a significant impact on their growth and development. Sweating is essential for the flow of water and minerals in plants, and it is highly influenced by air temperature and humidity. Greenhouses are structures that allow for the regulation of the climatic environment so that plants can thrive in it. To do this and ensure optimal management, greenhouses require sophisticated and accurate control. Controlling the microclimate in greenhouses requires a certain level of expertise, especially in sunny climates (arid and semi-arid region). The analysis of a greenhouse's response as a function of external climatic conditions, on the other hand, allows for a better understanding of its operation. Improved irrigation, ventilation, and heating systems, and therefore better climate control under cover, necessitate a more detailed analysis of the mechanisms driving the exchange (heat and mass) between interior air and the environment. It is also feasible to optimise fertilisation and spraying systems, as well as the agro-greenhouse system in general. Since these mechanisms are limiting factors that have a strong influence on production both in terms of quantity and quality, it now appears that good management of the greenhouse microclimate can both improve crop preservation and reduce costs incurred, this problem affects farmers (serrists) and greenhouse manufacturers jointly. The agricultural greenhouse's micro-climate control interface takes into consideration sunlight, temperature, humidity level, and external weather factors such as rain, wind direction, and wind speed. It intervenes on its own in response to the plant's needs, but the user can still make changes remotely using the sensor and actuator systems. Current agricultural greenhouse systems operate according to logical rules based on a binary system: if the temperature rises above a predetermined threshold, the automaton is triggered to refresh or reheat the ambient air. What we're attempting to create is a control law that allows us to optimise plant development while lowering energy expenses. Regardless of outside weather conditions, the technology would maintain constant temperatures and humidity levels in the agricultural greenhouse. The intelligent control of a greenhouse by fuzzy logic can solve most of these problems and obstacles, and here is where the real trouble lies. The modelling of an agricultural greenhouse (actual model), the modelling of a fuzzy controller, and the simulation of the model using real data from a specified site are all part of our paper's work (Dar el Beida Algeria) Our control logic for agricultural greenhouse climatic variables and parameters, as well as air conditioning, heating, and ventilation systems, is fuzzy. The utilisation of real data is critical since it allows us to test our model, add meaning to the simulation, and define the various controller gains and parameters. This mindset has changed in recent years. It's possible that the hazy command To occupy a minor position in the arsenal of today's engineer, without supplanting established approaches, and to be a helpful supplement in the case of agricultural greenhouses with difficult-to-identify systems or whose parameters fluctuate rapidly.

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