Creation of a model of automated traction control of shunting locomotives by using artificial intelligence methods - Oleksandr Gorobchenko; Denis Zaika (Збірник наукових праць Державного університету інфраструктури та технологій: серія "Транспортні системи і технології")
In the paper, a mathematical model of the automated traction transmission control system of the shunting locomotive was developed, using methods of fuzzy logic and the method of expert evaluations. The Mamdani algorithm was used for the proposed model. The algorithm includes the knowledge base of an intelligent system, which uses a production model to formalize and represent knowledge in memory, combining elements of logical and network management approaches. The resulting automated traction transmission control model of the shunting locomotive offers its optimal driving mode for a specific train and section. The model uses the generated fuzzy knowledge base. The result of the model calculation is a control signal for the movement of the shunting locomotive on 4 motors, using partially the 3rd and fully the 4th and 5th positions of the driver's controller. This mode of movement allows to reduce fuel consumption for shunting of the locomotive with partial loads on the traction electric transmission.