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Evaluation of the Reliability of Empirical Mathematical Models of Dynamic Systems Using Input Signal Shift Method
https://doi.org/10.17587/mau.26.111-118
Abstract
An algorithm is proposed that makes it possible to effectively detect the presence of correlated interference in experimental data used for parametric identification. The main problem leading to such interference is structural inconsistencies between models and real objects. Establishing the presence of correlated interference opens up opportunities for expanding identification tools. In this paper, the identification of correlated interference using the parametric identification method was carried out, while using a modified Newton method to minimize the objective functional. The results obtained from the numerical example demonstrate the effectiveness of the proposed method in detecting correlated interference, and also indicate that the values of the criteria contain information about the magnitude of the estimation errors. The results obtained in this scientific research work can be useful for further developments in the field of parametric identification and signal processing.
About the Authors
O. N. Korsun
State Research Institute of Aviation Systems; Moscow Aviation Institute (NRU)
Russian Federation
Russian Federation
O. N. Korsun, Dr. Sc. (Eng.), Professor, Head of the Scientific and Educational Center
Moscow, 125319
Moscow, 125993
M. H. Om
State Research Institute of Aviation Systems
Russian Federation
Russian Federation
Moung Htang Om, Сand. Tech. Sc, Post-doctoral Candidate
Moscow, 125319
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Review
For citations:
Korsun O.N., Om M.H. Evaluation of the Reliability of Empirical Mathematical Models of Dynamic Systems Using Input Signal Shift Method. Mekhatronika, Avtomatizatsiya, Upravlenie. 2025;26(3):111-118. https://doi.org/10.17587/mau.26.111-118
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