Zakovorotnyi O. Synthesis of automated rolling stock control system on the basis of geometric control theory and neural networks

Object of study: Control Processes traction rolling stock. The aim is to develop a decision support system driver for automated control system diesel train that is based on a generalized mathematical model, geometric control theory and neural networks can improve the energy performance of traction rolling stock. Methods: theory traction trains and electric traction, methods of geometric control theory, programming, mathematical modeling, artificial intelligence and neural networks. Theoretical and practical results: enhanced methodological basis for creating SPPRM adequate mathematical models and processes traffic speed rolling stock. The widespread scope geometric control theory based automation of analytical calculations and searching functions converting between variables nonlinear and linear models in the form Brunovsky. Grounded introduction to geometric control theory further search phase controls, which includes, in addition to finding optimal controls for level control channels, and even search for optimal control at the level of the object. Theory of new steady-plastic Hamming neural networks, Hebb and network-based Perceptron, which are able to recognize and learn new information. The results found implementation in enterprises and organizations involved in the operation, modernization and production of components of traction rolling stock. Scientific novelty: Scientific and applied solved the problem of developing a decision support system driver diesel train on the basis of geometric control theory and new neural network databases and knowledge that creates the theoretical premise of building automatic control systems and high-speed rolling stock can improve its energy performance. Field of use: the construction of automatic control systems of Ukrzaliznytsia traction rolling stock that will in real speed traffic and road conditions change manage schedules by train, using a minimal amount of energy resources and supporting a comfortable environment for passengers.