Neural network control for crushing-milling complex
The article examines issues of the artificial neural networks. They are applied for monitoring and control systems’ construction of crushing-milling complex in order to determine and support optimal electricity consumption mode of crushing and grinding aggregates. Issues related to the regulator’s structure selection and its training were resolved. For the practical solution of the tracking problem approximate NARMA model was proposed. Approximate NARMA is a model with a dedicated control component. It is shown that the application of the adjusted neural controller allows to reach more stable work of output area. This controller can also be applied in cases with random changes of input, thereby reducing electricity consumption of the complex.