Identification of models using analog sensitivity functions

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Applied Physics, Information Technologies and Engineering, APITECH 2020

Год издания: 2020

Идентификатор DOI: 10.1088/1742-6596/1679/3/032045

Аннотация: The paper proposes an algorithm for retrospective and adaptive estimation of sensitivity functions in relation to the problem of parametric identification of a dynamic model of an object. The proposed approach is based on the combined use of local and global sensitivity analysis methods. The algorithm is based on the use of analogsПоказать полностьюof sensitivity functions. They are not sensitivity functions in strict sense in the case of large parameter deviations. Analogs of sensitivity functions become their estimates with reduction deviations. The procedure for compressing the region of variation is based on the approach used in the selective coordinate averaging algorithm. The results are used for evaluating the sensitivity functions of the Monod model, and for parametric identification of the simple distillation process model using the adaptive least squares method. © Published under licence by IOP Publishing Ltd.

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Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1679, Is. 3

Номера страниц: 32045

ISSN журнала: 17426588

Издатель: IOP Publishing Ltd

Персоны

  • Voronov V.S. (Department of Informatics, Institute of Space and Information Technologies, Siberian Federal University, Krasnoyarsk, 660074, Russian Federation)
  • Rouban A.I. (Department of Informatics, Institute of Space and Information Technologies, Siberian Federal University, Krasnoyarsk, 660074, Russian Federation)

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