The paper investigates and evaluates the possibilities of using an artificial neural network. Attention is paid to the structural and operational features of the artificial neural networks, the learning processes used in them and their capabilities. The methods of application of artificial neural network for the purpose of control and diagnostics of dynamic systems of the electric drives are considered. A comparative analysis of the electric drive systems with PID regulators and neuroregulators was conducted. The expediency and necessity of improving the abilities of training artificial neural networks for adaptive control and diagnostics of the electric drives with incomplete description have been revealed, including the drives operating under random influences and dynamically changing modes. The main circumstances preventing the use of artificial neural networks, the laws of the choice of types and methods of optimization in the process of artificial neural networks (ANN) training and the lack of criteria for choosing the number of the neurons in the network are given. A review of well-known works devoted to the use of ANN in the electric drive systems, as well as a comparative analysis of the feasibility of using gradient and genetic methods of their training are carried out. The comparative analysis was carried out by summarizing the conclusions in various published works. Analysis shows that, in most cases, networks trained by genetic algorithms provide more accurate results, easier learning, and shorter duration. At the same time, in some cases, the use of the back propagation algorithm in the certain problems leads to better results. Thus, it can be stated that the use of the preferred algorithm depends on the formulation of the task.

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The requirement and the available resources of energy saving possibilities in the oregrinding technological process are substantiated. The known trends in energy saving in production enterprises are studied. The goal of the work is formulated to show the necessity of having distinct information about the reactive power produced by the synchronous motors and consumed by the induction motors operating in the given process. The reactive power consumption and its distribution at different overloads of the synchronous and induction motors are estimated. An algorithm is proposed, allowing to consider the changes in the reactive powers at changing the parameters of the synchronous and induction motors used in the process and the supply net so that the reactive powers required by induction motors are compensated by the synchronous motor.A diagram of the automated control system of the optimal distribution of the reactive power generated by the synchronous motors is proposed.

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