Abstract
The article is devoted to questions of synthesis of full-scale - model realizations of data series on the basis of natural data for modeling of controllable and uncontrollable influences at research of operating and projected control systems, and also in training systems of computer training. The possibility of formation of model effects on the basis of joint use of multivariate dynamic databases and natural data simulator is shown. Dynamic databases store information that characterizes the typical representative situations of systems in the form of special functions - generating functions. Multiple variability of dynamic databases is determined by the type of the selected generating function, the methods of obtaining parameters (coefficients) of this function, as well as the selected accuracy of approximation. The situation models recovered by generating functions are used as basic components (trends) in the formation of the resulting full-scale - model implementations and are input into the natural data simulator. The data simulator allows for each variant of initial natural data to form an implementation of the perturbation signal with given statistical properties on a given simulation interval limited by the initial natural implementation. This is achieved with the help of a two-circuit structure, where the first circuit is responsible for evaluation and cor-rection of initial properties of the natural signal, and the second - for iterative correction of deviations of properties of the final implementation from the specified ones. The resulting realizations reflect the properties of their full-scale components, which are difficult to describe by analytical models, and are supplemented by model values, allowing in increments to correct the properties to the specified ones. The given approach allows to form set of variants of course of processes on the basis of one situation with different set degree of uncertainty and conditions of functioning.
Highlights
The article is devoted to questions of synthesis of full-scale - model realizations of data series on the basis of natural data for modeling of controllable and uncontrollable influences at research of operating and projected control systems, and in training systems of computer training
Multiple variability of dynamic databases is determined by the type of the selected generating function, the methods of obtaining parameters of this function, as well as the selected accuracy of approximation
The data simulator allows for each variant of initial natural data to form an implementation of the perturbation signal with given statistical properties on a given simulation interval limited by the initial natural implementation
Summary
Статья посвящена вопросам синтеза натурно-модельных реализаций рядов данных на основе натурных данных для моделирования контролируемых и неконтролируемых воздействий при исследовании действующих и проектируемых управляющих систем, а также в обучающих системах компьютерного тренинга. Показана возможность формирования модельных воздействий на основе совместного использования многовариантных динамических баз данных и имитатора натурных данных. Восстановленные по генерирующим функциям модели ситуаций используются как базовые составляющие (тренды) при формировании итоговых натурно-модельных реализаций и поступают в имитатор натурных данных. Ключевые слова: натурный объект управления, многовариантные динамические базы данных, натурно-модельный подход, имитатор натурных данных, типопредставительные ситуации. С другой стороны, решение указанных задач требует наличия многих однотипных вариантов реализации натурных данных, которые не всегда имеет смысл хранить, либо необходимо практически бесконечное число вариантов статистически подобных реализаций. Возникает вопрос о формировании модельных реализаций на базе натурных рядов данных, причем на многовариантной основе [1]. Применение такого подхода позволит разнообразить вариантообразующие процедуры с вариантностью по воздействиям, по условиям и по преобразованиям
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