Experimental Data Processing for Nonlinear System Identification in MATLAB/Simulink
pdf (Georgian)

Keywords

nonlinear systems
parametric identification
Fourier coefficients
computer modeling system Matlab/Simulink

How to Cite

Shanshiashvili, B., Davitashvili, I., & Mchedlishvili, N. (2026). Experimental Data Processing for Nonlinear System Identification in MATLAB/Simulink. International Scientific-Practical Conference: „Modern Challenges and Achievements in Information and Communication Technologies“ Transactions, 4, 501-505. https://papers.4science.ge/index.php/mcaaict/article/view/461

Abstract

The objective of this study is to address the problem of parametric identification of nonlinear dynamic systems by processing experimental data when the system under investigation is subjected to a harmonic signal with variable frequency. To solve the problem of parameter identification of nonlinear dynamic systems, it is necessary to: extract one or several periods of forced oscillations obtained in the steady state on the objects output for determination the Fourier coefficients, with the aim of their further use for parametric identification of the object. To achieve this objective, the MATLAB computational modeling environment and its integrated structural modeling platform Simulink were employed. A software code was developed to automate the process, structural modeling schemes were created, and methods for determining Fourier coefficients-specifically the fft function and the FFT block-were applied. The proposed methodology was verified through a case study involving a specific nonlinear dynamic system.

pdf (Georgian)

References

Shanshiashvili B., Rigishvili T. Parameter Identification of Block-Oriented Nonlinear Systems in the Frequency Domain. ScienceDirect. IFAC PapersOnLine. Volume 53, Issue 2, 2020, pp. 10695–10700. Part of the special issue, 21st IFAC World Congress: Berlin, Germany, 11–17 July 2020. Doi.org/10.1016/j.ifacol.2020.12.2843.

Shanshiashvili B., Avazneli, B. Identification of Nonlinear Dynamic Systems Structured by Expanded Wiener Model. In: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 630, pp. 546-554. 2021. Springer, https://doi.org/10.1007/978-3-030-85874-2_58.

Shanshiashvili B. Identification of Closed-Loop Nonlinear Systems Using One Class of Block-Oriented Models. Articles of the International Scientific-Practical Conference “Modern Challenges And Achievements Of Information And Communication Technologies” – 2023. (Georgia, Tbilisi, 12-13 October 2023). pp.145-153. Publishing House “Technical University”, 2023, http://www.gtu.ge yvela ufleba daculia. am wignhttps://gtu.ge/ims/pdf/docs/collection-of-scientific-works-2023.pdf

Shanshiashvili B. Parameter Identification of One Class of Nonlinear Systems Using Hammerstein Model with Feedback. PCI’ 2023. V International Conference “Problems of Cybernetics and Informatics” (Baku, Azerbaijan, August 28-30, 2023). Proceedings of PCI’ 2023. Volume 2. 5 pp. DOI: https://doi.org/10.54381/pci2023.10

Shanshiashvili B. Identification of Nonlinear Systems in Frequency Domain Using Hammerstein Models. Articles of the International Scientific-Practical Conference Modern Challenges and Achievements of Information and Communication Technologies – 2024. (1-2 November 2024, Tbilisi, Georgia). Publishing House “Technical University”, 2024, pp. 332-339. https://gtu.ge/ims/pdf/docs/collection-of-works.pdf.

ნ.მჭედლიშვილი, ი.დავითაშვილი. დაპროგრამება Matlab გარემოში. მეორე გამოცემა. საქ. ტექნიკური უნივერსიტეტი, თბილისი, 2021.

ნინო მჭედლიშვილი, ირმა დავითაშვილი. საინჟინრო სისტემების მო¬დე¬ლირება და სიმულაცია Simulink და Simscape-ის გამოყენებით. 2025.