Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems
This paper presents one possible application of generalized quasi-orthogonal functional networks in the sensitivity analysis of complex dynamical systems. First, a new type of first order (k = 1) generalized quasi-orthogonal polynomials of Legendre type via classical quasi-orthogonal polynomials was...
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Format: | Article |
Language: | English |
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Kaunas University of Technology
2022-08-01
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Series: | Elektronika ir Elektrotechnika |
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Online Access: | https://eejournal.ktu.lt/index.php/elt/article/view/31110 |
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author | Sasa S. Nikolic Dragan S. Antic Nikola B. Dankovic Aleksandra A. Milovanovic Darko B. Mitic Miroslav B. Milovanovic Petar S. Djekic |
author_facet | Sasa S. Nikolic Dragan S. Antic Nikola B. Dankovic Aleksandra A. Milovanovic Darko B. Mitic Miroslav B. Milovanovic Petar S. Djekic |
author_sort | Sasa S. Nikolic |
collection | DOAJ |
description | This paper presents one possible application of generalized quasi-orthogonal functional networks in the sensitivity analysis of complex dynamical systems. First, a new type of first order (k = 1) generalized quasi-orthogonal polynomials of Legendre type via classical quasi-orthogonal polynomials was introduced. The short principle to design generalized quasi-orthogonal polynomials and filters was also shown. A generalized quasi-orthogonal functional network represents an extension of classical orthogonal functional networks and neural networks, which deal with general functional models. A sequence of the first order (k = 1) generalized quasi-orthogonal polynomials was used as a new basis in the proposed generalized quasi-orthogonal functional networks. The proposed method for determining the parameter sensitivity of complex dynamical systems is also given, and an example of a complex industrial system in the form of a tower crane was considered. The results obtained have been compared with different methods for parameter sensitivity analysis. |
first_indexed | 2024-04-11T14:16:51Z |
format | Article |
id | doaj.art-ccdbff5bc7b64b909b17fbacacbfbf0d |
institution | Directory Open Access Journal |
issn | 1392-1215 2029-5731 |
language | English |
last_indexed | 2024-04-11T14:16:51Z |
publishDate | 2022-08-01 |
publisher | Kaunas University of Technology |
record_format | Article |
series | Elektronika ir Elektrotechnika |
spelling | doaj.art-ccdbff5bc7b64b909b17fbacacbfbf0d2022-12-22T04:19:17ZengKaunas University of TechnologyElektronika ir Elektrotechnika1392-12152029-57312022-08-01284192610.5755/j02.eie.3111036364Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical SystemsSasa S. Nikolic0Dragan S. Antic1https://orcid.org/0000-0002-5880-5173Nikola B. Dankovic2https://orcid.org/0000-0003-0986-5695Aleksandra A. Milovanovic3Darko B. Mitic4https://orcid.org/0000-0001-9483-0176Miroslav B. Milovanovic5https://orcid.org/0000-0003-0535-0790Petar S. Djekic6https://orcid.org/0000-0001-9506-7301Department of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaDepartment of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaDepartment of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaDepartment of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaDepartment of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaDepartment of Control Systems, Faculty of Electronic Engineering, University of Nis, SerbiaThe Academy of Applied Technical and Preschool Studies-Nis, SerbiaThis paper presents one possible application of generalized quasi-orthogonal functional networks in the sensitivity analysis of complex dynamical systems. First, a new type of first order (k = 1) generalized quasi-orthogonal polynomials of Legendre type via classical quasi-orthogonal polynomials was introduced. The short principle to design generalized quasi-orthogonal polynomials and filters was also shown. A generalized quasi-orthogonal functional network represents an extension of classical orthogonal functional networks and neural networks, which deal with general functional models. A sequence of the first order (k = 1) generalized quasi-orthogonal polynomials was used as a new basis in the proposed generalized quasi-orthogonal functional networks. The proposed method for determining the parameter sensitivity of complex dynamical systems is also given, and an example of a complex industrial system in the form of a tower crane was considered. The results obtained have been compared with different methods for parameter sensitivity analysis.https://eejournal.ktu.lt/index.php/elt/article/view/31110orthogonal polynomialssensitivity analysisfunctional networkstower crane |
spellingShingle | Sasa S. Nikolic Dragan S. Antic Nikola B. Dankovic Aleksandra A. Milovanovic Darko B. Mitic Miroslav B. Milovanovic Petar S. Djekic Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems Elektronika ir Elektrotechnika orthogonal polynomials sensitivity analysis functional networks tower crane |
title | Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems |
title_full | Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems |
title_fullStr | Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems |
title_full_unstemmed | Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems |
title_short | Generalized Quasi-Orthogonal Functional Networks Applied in Parameter Sensitivity Analysis of Complex Dynamical Systems |
title_sort | generalized quasi orthogonal functional networks applied in parameter sensitivity analysis of complex dynamical systems |
topic | orthogonal polynomials sensitivity analysis functional networks tower crane |
url | https://eejournal.ktu.lt/index.php/elt/article/view/31110 |
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