Control of heating processes in electro transport mechatronic system using sigmoidal feed forward neural network

• Autorzy: Beinarts I. , Levchenkov A. , Balckars P.
• Języki publikacji: EN

Abstrakty

EN

In this article interest is concentrated on the climate parameters optimization in passengers’ interior of mechatronic systems (public electric transportation vehicles- train, tram or trolleybus). Idea is to use feed forward artificial neural network to create an algorithm and coordination mechanism for heating system parameters control to save electrical energy, and to increase the level of comfort for passengers. A special interest for investigations and further development is devoted to intelligent HVAC system allowing more flexible control of the system’s compressor, fan and heater operation, and, therefore, improvement of efficiency and energy saving. This paper provides the mathematical model and algorithm for optimal control of the climate control system.

Słowa kluczowe

EN

neural networks; public transport; heating process

PL

sieci neuronowe; transport publiczny; proces nagrzewania

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Acta Mechanica et Automatica
• Rocznik: 2008
• Tom: Vol. 2, no. 3
• Strony: 14--18
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Beinarts I.

autor

Levchenkov A.

autor

Balckars P.

• Riga Technical University, Kronvalda blvd. 1-202, Riga, LV-1010, Latvia,

Bibliografia

• 1. Beinarts I., Levchenkov A. (2007), Intelligent Systems for Transport Climate Parameters Optimization Using Multi Criteria Decision Making, Proceedings of 48th RTU international scientific conference “Power and Electrical Engineering”, RTU press, Latvia, Riga.
• 2. Beinarts I., Levchenkov A. (2008), Usage of Fuzzy Logic Controller for Passengers’ Interior Heating System of Railway Electric Transport”. Proceedings of 16th International Symposium “EURNEX-Zel2008”, Slovakia, Zilina.
• 3. Bose B. K. (2002), Modern Power Electronics and AC Drives, Prentice Hall PTR, Upper Saddle River.
• 4. Greivulis J., Firago B. (1993), Principles of Electrical Drives in Questions and Answers, RTU press, Latvia, Riga.
• 5. Haykin S. (1998), Neural Networks: A Comprehensive Foundation, Prentice Hall.
• 6. Kecman V. (2001), Learning and Soft Computing: Support Vector Machines. Neural Networks, and Fuzzy Logic Models, Massachusetts Institute of Technology.
• 7. Kröse B., Smagt P. (1996), An Introduction to Neural Networks, The University of Amsterdam.
• 8. Leonhard W. (1996), Control of Electrical Drives, Springer-Verlag, Berlin.
• 9. Murphy J. M. D., Turnbull F. G. (1985), Power Electronic Control of AC Motors, Pergamon Press, Oxford.
• 10. Ribickis L., Rankis I. (1996), Electrical Drive, RTU. Latvia, Riga.
• 11. Sauer H. J., Howell R. H. (1994), Principles of Heating Ventilating and Air Conditioning, ASHRAE, Atlanta.