Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805

This article describes the process of frictional self-oscillations in the electric mine locomotive, which arise as a consequence of the dynamic instability of the control object and the nonlinearity of the mechanical characteristics of the load. These fluctuations lead to increased wear of wheels and rails gearboxes. To prevent frictional self-oscillations in the electromechanical system proposed closed-loop control that is based onthe feedforward neural network structure NN3-10-1 type perceptron. The methods for training neural networks, their advantages and disadvantages. The graphs of transient electric mine locomotive without a control system and neural network control system. The analysis of the resulting graphs.


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