| Summary: | Background. The relevance of the work is due to the possibility of increasing energy efficiency with
the help of neural network automatic control systems, since the existing models of ventilation and air conditioning systems
and their automatic control systems consider individual processes occurring in the ventilation system and do not
take into account all control channels and disturbances, the relationship of adjustable parameters, spatial distribution
points of application of influences and variability of the structure of the control object. The aim of the work is to reduce
the cost of electricity by improving the efficiency of energy use, as well as improving the quality of management.
Materials and methods. To achieve the goals set, the methods of computer neural network modeling were used.
Results and conclusions. A neural network model of an automatic control system for the process of air conditioning of
a buried structure was built, which operates under the influence of stepwise disturbing influences using neural network controllers that control by the method of "detection of discord". Preliminary calculations of the energy efficiency of
the proposed neural network control in real systems show that the saving of electrical energy in comparison with traditional
PID control reaches 7–10 % depending on the mode of operation of the system, which in large-scale systems is
expedient and in demand from an economic point of view.
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