Please use this identifier to cite or link to this item: https://dspace.mnau.edu.ua/jspui/handle/123456789/14266
Title: Method of polynomial predictive control of fail-safe operation of technical systems
Authors: Атаманюк, Ігор Петрович
Atamanyuk, Igor
Kondratenko, Yuriy
Шебанін, В’ячеслав Сергійович
Shebanin, Vyacheslav
Mirgorod, Vladimir
Keywords: Method of predictive control
Random sequence
Microelectronics
Stochastic systems
Controlled parameter
Nonlinear estimates
Numerical experiments
Predictive control
Probability of fails
Random sequence
Stochastic nature
Technical systems
Computer aided design
Issue Date: 2015
Publisher: Mykolaiv National Agrarian University
Citation: Atamanyuk, I., Kondratenko, Y., Shebanin, V., & Mirgorod, V. (2015). Method of polynomial predictive control of fail-safe operation of technical systems // Paper presented at the Proceedings of 13th International Conference: The Experience of Designing and Application of CAD Systems in Microelectronics, CADSM 2015, 248-251. doi:10.1109/CADSM.2015.7230848
Abstract: In this paper there was obtained a method of the assessment of the probability of fail-safe operation of technical systems in the future instants of time. The method is based on the algorithm for modeling a posteriori nonlinear random sequence of change of values of the controlled parameter which is imposed a limitation of belonging to a certain range of possible values. The probability of fail-safe operations is defined as the ratio of the number of realizations that fell in the allowable range to the total number of them, formed as a result of the numerical experiment. The realization of a posteriori random sequence is an additive mixture of optimal from the point of view of mean-square nonlinear estimate of the future value of the parameter analyzed and of the value of a random variable, which can not be predicted due to the stochastic nature of the parameter. The model of a posteriori random sequence is based on the Pugachev's canonical expansion. The method offered does not impose any significant constraints on the class of random sequences analyzed (linearity, stationarity, Markov behavior, monotoneness, etc.). © 2015 Lviv Polytechnic National University.
Description: Повний текст статті доступний за посиланням https://ieeexplore.ieee.org/document/7230848/citations#citations
URI: https://dspace.mnau.edu.ua/jspui/handle/123456789/14266
Appears in Collections:Публікації науково-педагогічних працівників МНАУ у БД Scopus
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