Abstract
This paper presents the development of the mathematical model and system of parametrical identification for the ecopyrogenesis (EPG) plant as a complex multi-coordinate control object on the basis of soft computing techniques. The synthesis procedure of the main parts of the EPG plant’s mathematical model, including its fuzzy parametrical identification system, adaptive-network-based fuzzy inference system for calculating of multiloop circulatory system (MCS) temperature and Mamdani type fuzzy inference system for calculating of reactor load level, is presented. The analysis of computer simulation results in the form of static and dynamic characteristics graphs of the EPG plant confirms the high adequacy of the developed complex neuro-fuzzy model to the real processes. The developed mathematical model with parametrical identification based on neuro-fuzzy technologies gives the opportunity to investigate the behavior of the given complex control object in steady and transient modes, in particular, to synthesize and adjust the intelligent controllers of the multi-coordinate automatic control system of the EPG plant.
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Kondratenko, Y.P., Kozlov, O.V., Kondratenko, G.V., Atamanyuk, I.P. (2018). Mathematical Model and Parametrical Identification of Ecopyrogenesis Plant Based on Soft Computing Techniques. In: Berger-Vachon, C., Gil Lafuente, A., Kacprzyk, J., Kondratenko, Y., Merigó, J., Morabito, C. (eds) Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Studies in Systems, Decision and Control, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-319-69989-9_13
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