DEVELOPMENT OF INTELLECTUAL COMPLEX FOR ADAPTIVE MANAGEMENT OF MICROCLIMATE PARAMETERS OF FLOUR STORAGE PROCESSES
In the modern socio-economic and geopolitical development of Russia, the development of agriculture and food industry comes to the fore. As a result, the requirements to the quality and safety of the finished product increase many times, which significantly affects its competitiveness. Among the many branches of the food industry, the most important role belongs to the milling. Its products are extremely popular among the population of our country. This means that the quality of the finished product has special requirements. Storage of flour is one of the most important stages of the technological process of flour production. Bulk storage of flour in silos is a complex technological process, which is largely affected by the environment (temperature, pressure, humidity, etc.). If you do not take appropriate measures, then under the influence of these factors, the technological properties of flour will change and go beyond the permissible values. Today, neural networks can solve a wide range of data processing and analysis tasks - pattern recognition and classification, prediction and management. An important feature of neural networks is the ability to learn andgeneralize the accumulated knowledge. Trained on a limited set of data, the network is then able to generalize theinformation received and process data not used in its training. This article presents the development of an intelligent complex for adaptive control of microclimate parameters of flour storage processes and improving the efficiency of management of technological processes of flour storage through the use of intelligent technologies. The model of microclimate parameters in the silo is shown, taking into account multiple relationships between the process parameters. The expediency of using intelligent control technologies based on the development of a neural network controller for automation of microclimate parameters control is substantiated. A mathematical model of the control object was developed taking into account the inherent internal relationships between the parameters of the technological regime and external perturbing factors. Processing of research results was carried out using the software «MatLab».