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Automatic Search Method of Efficiency Extremum for a Multi-stage Processing of Raw Materials

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2019)

Abstract

The article deals with the theoretical and practical problem of optimal control of raw material processing processes with the continuous consumption of raw materials and energy. Based on the positions of the efficiency theory, the choice of a universal efficiency factor for a selected class of processes has been made, with taking into account resource efficiency, quality indicators of the finished product, productivity of the technological system. The production system model is described including the transporting part, the processing part and implementation modules of control functions. The automatic search method of the extremum of the resource efficiency at the multi-stage processing with continuous supply of raw materials on the basis of the process calculation model is developed. Applying an efficiency factor as an optimization criterion allows making up optimization in a global sense. Within the method borders, the calculation algorithm of the system resources efficiency factor and the extremum search algorithm are proposed. The method efficiency is confirmed by the results of modeling the technological station’s operation with three sequence heating stages of the raw material. Each stage is characterized by consumption cost of equipment resources, energy and increment of the output product cost. The efficiency maximum search has a satisfactory timetable, is stable and can be used at real time control of the technological stations.

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Correspondence to Igor Konokh .

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Konokh, I., Oksanych, I., Istomina, N. (2020). Automatic Search Method of Efficiency Extremum for a Multi-stage Processing of Raw Materials. In: Lytvynenko, V., Babichev, S., Wójcik, W., Vynokurova, O., Vyshemyrskaya, S., Radetskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent Systems and Computing, vol 1020. Springer, Cham. https://doi.org/10.1007/978-3-030-26474-1_17

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