Rail transport electric drive with intelligent control system

Abstract

Purpose. The study of the conditions for the occurrence of frictional self-oscillations, the synthesis of a neuroregulator eliminating self-oscillation, the development of a system for automatic control of the of railway transport speed depending on the curvature of the track on the basis of computer vision technology. Methodology. Mathematical analysis and modeling. Findings. The paper presents the results of the development and research of an intelligent control system for the electric drive of a DS3 mainline electric locomotive. The developed systems have a single easily implemented motor speed feedback, which does not create difficulties in physical implementation. It is noted that a common feature of the electric drive of rail transport is a nonlinear load characteristic. It is shown that, under certain combinations of parameters, frictional self-oscillations are possible in the traction electric drive. Effective elimination of frictional self-oscillations is done  by synthesizing the system with a neuroregulator. The neural network has three input neurons that receive a vector of input signals in the form of a voltage signal, a signal of the motor speed value of the current and previous energy speed values. The number of neurons in the hidden layer of the system is 20 and there is one output neuron.The control actions for the frequency converter are formed on the output neuron. Neural networks of this type are designated NN3-20-1. The genetic algorithm method is used for all optimization of neural network parameters. The simulation model of the electric drive of rail transport has the integration of a computer vision unit. Increasing the level of automation and safety of rail vehicles is possible on the basis of computer vision. A feature of this structure is the presence of an NN neural regulator in it. NN ensures the specified quality of the transient process over the entire load range and when the operating point is located on a falling section. A system for automatic control of the speed of rail vehicles depending on the curvature of the track has been developed to increase the level of automation and traffic safety. Modeling of the system showed its efficiency, which is manifested in a decrease in the speed of rail vehicles when moving along a section of track with curvature. Originality.  Effective elimination of frictional self-oscillations due to the use of a neuroregulator. Practical value.  A system for automatically adjusting the speed of rail transport depending on the curvature of the track has been developed to increase the level of automation and traffic safety.