novtexmechМехатроника, автоматизация, управлениеMekhatronika, Avtomatizatsiya, Upravlenie1684-64272619-1253Commercial Publisher «New Technologies»10.17587/mau.26.111-118novtexmech-1707Research ArticleСИСТЕМНЫЙ АНАЛИЗ, УПРАВЛЕНИЕ И ОБРАБОТКА ИНФОРМАЦИИSYSTEM ANALYSIS, CONTROL AND INFORMATION PROCESSINGОценка достоверности эмпирических математических моделей динамических систем методом сдвига входного сигналаEvaluation of the Reliability of Empirical Mathematical Models of Dynamic Systems Using Input Signal Shift MethodКорсунО. Н.KorsunO. N.

О. Н. Корсун, д-р техн. наук, проф., руководитель научно-образовательного центра

г. Москва

O. N. Korsun, Dr. Sc. (Eng.), Professor, Head of the Scientific and Educational Center

Moscow, 125319

Moscow, 125993

ОмМ. ХOmM. H.

Моунг Хтанг Ом, канд. техн. наук, докторант

г. Москва

Moung Htang Om, Сand. Tech. Sc, Post-doctoral Candidate

Moscow, 125319

ГосНИИАС; МАИ (НИУ)РоссияState Research Institute of Aviation Systems; Moscow Aviation Institute (NRU)Russian FederationМАИ (НИУ)РоссияState Research Institute of Aviation SystemsRussian Federation202513032025263111118Copyright © Commercial Publisher «New Technologies», 20252025Commercial Publisher «New Technologies»Commercial Publisher «New Technologies»https://mech.novtex.ru/jour/about/submissions#copyrightNoticehttps://mech.novtex.ru/jour/article/view/1707

Предложен алгоритм, позволяющий эффективно при проверке достоверности модели динамического объекта обнаруживать наличие в экспериментальных данных помехи, коррелированной с полезным сигналом. Основной проблемой, приводящей к возникновению таких помех, являются структурные несоответствия между моделями и реальными объектами. Установление факта наличия коррелированной помехи открывает возможности для расширения инструментов идентификации. В настоящей работе проведена идентификация коррелированных помех с использованием метода параметрической идентификации, при этом применялся модифицированный метод Ньютона для минимизации целевого функционала. Результаты, полученные с помощью математического моделирования на примере движения летательного аппарата, демонстрируют эффективность предложенного метода в выявлении коррелированных помех, а также указывают на то, что значения предложенных критериев обнаружения помехи содержат информацию о значениях погрешностей оценивания. Результаты исследования могут быть полезны для дальнейших разработок в области параметрической идентификации и обработки сигналов.

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.

коррелированные помехиструктурные несоответствиясдвиг входного сигналапараметрическая идентификацияпогрешности оцениванияcorrelated interferencestructural inconsistenciesinput signal shiftparametric identificationestimation errorsReferencesKlein V., Morelli E. A. Aircraft System Identification: Theory and Practice, Reston, AIAA, 2006, 499 р.Klein V., Morelli E. A. Aircraft System Identification: Theory and Practice, Reston, AIAA, 2006, 499 р.Korsun O. N., Poplavsky B. K. Approaches for Flight Tests Aircraft Parameter Identification, 29th Congress of the International Council of the Aeronautical Sciences, ICAS 2014, ICAS 2014 CD-ROM PROCEEDINGS,1804, Bonn, 2014.Korsun O. N., Poplavsky B. K. Approaches for Flight Tests Aircraft Parameter Identification, 29th Congress of the International Council of the Aeronautical Sciences, ICAS 2014, ICAS 2014 CD-ROM PROCEEDINGS,1804, Bonn, 2014.Hale L. E., Patil M., Roy Ch. J. Aerodynamic Parameter Identification and Uncertainty Quantification for Small Unmanned Aircraft, AIAA 2015-1538, Session: Advances in UAS Technologies II, 2015, available at: https://doi.org/10.2514/6.2015-1538.Hale L. E., Patil M., Roy Ch. J. Aerodynamic Parameter Identification and Uncertainty Quantification for Small Unmanned Aircraft, AIAA 2015-1538, Session: Advances in UAS Technologies II, 2015, available at: https://doi.org/10.2514/6.2015-1538.Bucharles A., Comer C., Hardier G., Jacquier B., Janot A., Le Moing T., Siren C., Toussaint C., Vacher P. An Overview of Relevant Issues for Aircraft Model Identification, Aerospace Lab, 2012, vol. 4, pp. 1—21 <hal-01183676>.Bucharles A., Comer C., Hardier G., Jacquier B., Janot A., Le Moing T., Siren C., Toussaint C., Vacher P. An Overview of Relevant Issues for Aircraft Model Identification, Aerospace Lab, 2012, vol. 4, pp. 1—21 <hal-01183676>.Tischler M. B. System identification methods for aircraft flight control development and validation, Technical Memorandum (TM), Aeroflightdynamics Directorate, U. S. Army ATCOM, Ames Research Center, Moffett Field, California, 1995, NASA-TM-110369.Tischler M. B. System identification methods for aircraft flight control development and validation, Technical Memorandum (TM), Aeroflightdynamics Directorate, U. S. Army ATCOM, Ames Research Center, Moffett Field, California, 1995, NASA-TM-110369.Hällqvist R., Eek M., Brown R., Kraus P. Methods for automating model validation: steady-state identification applied on gripen fighter environmental control system measurements, 30th Congress of the international council of the aeronautical sciences, 2016.Hällqvist R., Eek M., Brown R., Kraus P. Methods for automating model validation: steady-state identification applied on gripen fighter environmental control system measurements, 30th Congress of the international council of the aeronautical sciences, 2016.Ghoreyshi M., Jirasek A., Seidel J. Computational validation and system identification modeling for stability and control predictions, The Aeronautical Journal, 2023, vol. 127, no. 1311, pp. 831—851, doi: 10.1017/aer.2022.94.Ghoreyshi M., Jirasek A., Seidel J. Computational validation and system identification modeling for stability and control predictions, The Aeronautical Journal, 2023, vol. 127, no. 1311, pp. 831—851, doi: 10.1017/aer.2022.94.Battipede M., Cassaro M., Gili P., Gunetti P. Modeling and validation of aircraft mathematical models for the development of an innovative Flight Management System, CEAS 2011 The International Conference of the European Aerospace Societies, Venezia, 2011, pp. 1—10.Battipede M., Cassaro M., Gili P., Gunetti P. Modeling and validation of aircraft mathematical models for the development of an innovative Flight Management System, CEAS 2011 The International Conference of the European Aerospace Societies, Venezia, 2011, pp. 1—10.Dorobantu A., Balas G. J., Georgiou T. T. Validating aircraft models in the gap metric, Journal of Aircraft, 2014, vol. 51, no. 6, pp. 1665—1672, available at: https://doi.org/10.2514/1.C032580.Dorobantu A., Balas G. J., Georgiou T. T. Validating aircraft models in the gap metric, Journal of Aircraft, 2014, vol. 51, no. 6, pp. 1665—1672, available at: https://doi.org/10.2514/1.C032580.Hu H. W., Kao Н. Model Validation of an Ultralight Aircraft using Experimental Modal Analysis, Journal of Aeronautics, Astronautics and Aviation, 2009, Series А, vol. 41, no. 4, pp. 271—281, available at: https://doi.org/10.6125/JoAAA.200912_41(4).08.Hu H. W., Kao Н. Model Validation of an Ultralight Aircraft using Experimental Modal Analysis, Journal of Aeronautics, Astronautics and Aviation, 2009, Series А, vol. 41, no. 4, pp. 271—281, available at: https://doi.org/10.6125/JoAAA.200912_41(4).08.Carlsson M. Methods for Early Model Validation, Ph.D. dissertation, Linköping, Linköping University, 2013, 118 p.Carlsson M. Methods for Early Model Validation, Ph.D. dissertation, Linköping, Linköping University, 2013, 118 p.Eyre Ch., Brierley В. Performance Model Validation For Long-Endurance Unmanned Aircraft Using Mach VS. CL Test Method, 47th Annual International Symposium of the Society of Flight Test Engineers 2016, 2016, pp. 125—134.Eyre Ch., Brierley В. Performance Model Validation For Long-Endurance Unmanned Aircraft Using Mach VS. CL Test Method, 47th Annual International Symposium of the Society of Flight Test Engineers 2016, 2016, pp. 125—134.Dorobantu A., Seiler P. J., Balas G. J. Validating uncertain aircraft simulation models using flight test data, AIAA Atmospheric Flight Mechanics (AFM) Conference, Boston, MA, United States, 2013.Dorobantu A., Seiler P. J., Balas G. J. Validating uncertain aircraft simulation models using flight test data, AIAA Atmospheric Flight Mechanics (AFM) Conference, Boston, MA, United States, 2013.Meister J., Schacher S., Wunderli J.-M., Empa В. Sc. Validation of three aircraft noise calculation models, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600 Dubendorf, Switzerland.Meister J., Schacher S., Wunderli J.-M., Empa В. Sc. Validation of three aircraft noise calculation models, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600 Dubendorf, Switzerland.Giladi R. Munachi E. Validating Aircraft Noise Models, Proceedings 2020, vol. 59,no. 12, available at: https://doi.org/10.3390/proceedings2020059012.Giladi R. Munachi E. Validating Aircraft Noise Models, Proceedings 2020, vol. 59,no. 12, available at: https://doi.org/10.3390/proceedings2020059012.Grauer J. A., Morelli E. A. Parameter Uncertainty for Aircraft Aerodynamic Modeling using Recursive Least Squares, AIAA Atmospheric Flight Mechanics Conference, 2016, available at: https://doi.org/10.2514/6.2016-2009.Grauer J. A., Morelli E. A. Parameter Uncertainty for Aircraft Aerodynamic Modeling using Recursive Least Squares, AIAA Atmospheric Flight Mechanics Conference, 2016, available at: https://doi.org/10.2514/6.2016-2009.Orellana R., Carvajal R., Escárate P., Agüero J. C. On the Uncertainty Identification for Linear Dynamic Systems Using Stochastic Embedding Approach with Gaussian Mixture Models, Sensors, 2021, vol. 21, no. 11, pp. 3837, available at: https://doi.org/10.3390/s21113837.Orellana R., Carvajal R., Escárate P., Agüero J. C. On the Uncertainty Identification for Linear Dynamic Systems Using Stochastic Embedding Approach with Gaussian Mixture Models, Sensors, 2021, vol. 21, no. 11, pp. 3837, available at: https://doi.org/10.3390/s21113837.Hale L. E. Aerodynamic Uncertainty Quantification and Estimation of Uncertainty Quantified Performance of Unmanned Aircraft Using Non-Deterministic Simulations, Ph.D. dissertation: Virginia Polytechnic Institute and State University, Virginia, 2016, 111 p.Hale L. E. Aerodynamic Uncertainty Quantification and Estimation of Uncertainty Quantified Performance of Unmanned Aircraft Using Non-Deterministic Simulations, Ph.D. dissertation: Virginia Polytechnic Institute and State University, Virginia, 2016, 111 p.Van Der Merwe R., Wan E. A. The Unscented Particle Filter, Advances in Neural Information Processing Systems, 2001, vol. 14.Van Der Merwe R., Wan E. A. The Unscented Particle Filter, Advances in Neural Information Processing Systems, 2001, vol. 14.Korsun O. N., Om M. H. The practical rules for aircraft parameters identification based on flight test data, Metascience in Aerospace, 2024, vol. 1, no. 1, pp. 53—65, doi: 10.3934/mina.2024003.Korsun O. N., Om M. H. The practical rules for aircraft parameters identification based on flight test data, Metascience in Aerospace, 2024, vol. 1, no. 1, pp. 53—65, doi: 10.3934/mina.2024003.Gonzalez R. C., Cacace J. Identification of Aircraft Dynamics with Correlated Noise, Journal of Aircraft, 2018.Gonzalez R. C., Cacace J. Identification of Aircraft Dynamics with Correlated Noise, Journal of Aircraft, 2018.Jategaonkar R. V. Identification of the aircraft system: a time domain meth-odology, Reston, American Institute of Aeronautics and Astronautics, 2006.Jategaonkar R. V. Identification of the aircraft system: a time domain meth-odology, Reston, American Institute of Aeronautics and Astronautics, 2006.

The authors declare that there are no conflicts of interest present.