Information and communication technologies for intelligent control of ground unmanned multipur-pose vehicles

At present, there is a situation when the practice of creating modern devices, units and systems of ground unmanned vehicles (GUV) has preceded the theory of information analysis and synthesis of complex systems. Some existing solutions for the information support of the GUV need to be generalized, standardized and unified, the definition of new special requirements for the creation of computer systems and networks in transport should be made. Therefore, it is necessary and actual to develop information and communication technology for intelligent control of multi-purpose GUV. Goal. The purpose of the article is to develop information and communication technology for intelligent control of multi-purpose GUV, which work in conditions of intensive loads, difficult operating conditions, increased responsibility of mechanisms, resulting in reduced human losses and energy consumption, increased machine reliability and control accuracy. Methodology. The methodology of tasks is based on the use of a synergetic approach to the creation of information and communication technology for intelligent control of multi-purpose GUV, as the development of a systematic approach taking into account the adaptation and integration of the vehicle to transport infrastructure and/or rough terrain. The principles of synergetics underlie the construction of mechatronic systems – a combination in one unit of components of different technical nature (mechanical, electrical, computer), which adaptively interact with the external environment as a single functional and structural organism. The synergetic approach deals with phenomena and processes, as a result of which the system – as a whole – may have properties that none of the parts has. Results. The concept of intelligent control of multi-purpose GUV on the basis of artificial hybrid neuro-phase regulators with the use of cloud computing services and deep learning technology is proposed, substantiated and implemented, which allows to qualitatively increase the efficiency of both one vehicle and the transport system on the base combining a synergetic approach and evolutionary methods of learning multilayer artificial neural networks by objectively forming the architecture of these networks on the basis of learning functionalities and appropriate control objectives. Originality. Use of cloud computing services based on deep learning for intelligent control technology of GUV. Practical value. The proposed information and communication technology of intelligent control of multi-purpose GUV will significantly reduce energy consumption, psychophysical stress on crew members, as well as increase the accuracy of location.