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Passengers’ Interior Climate Parameters Optimization Using Intelligent Control with Neural Networks

By Ivars Beinarts and Anatolijs Ļevčenkovs


The main idea of this paper is to use neural networks and intelligent agents to create an algorithm and coordination mechanism for climate parameters control to save electrical energy and keep high comfort level in the object. Interest is concentrated on the climate parameters optimization in passengers’ interior of public electric transportation vehicles. The article presents mathematical problem using intelligent agents in mechatronics problems for climate parameters optimal control. The methods of the problem solving and structure of problem solving algorithm are given in the article. A special interest for investigations and further development is devoted to intelligent heating, ventilation and air condition systems allowing more flexible regulation of the system’s compressor, fan and heater operation, and, therefore, improvement of efficiency and energy saving. The elaborated control system model using neural networks can be used for sustaining microclimate in different facilities, buildings and public electric transportation. There are main conclusions at the end of article

Topics: neural networks, intelligent control, mechatronic system, energy saving, climate control
Publisher: Chair of Automatic Control in Transport, Faculty of Transport, Silesian University of Technology
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