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Research Article | Open Access

Analyzing the fractional Chen attractor via controlled interpolative metric contractions

Ekber Girgin1Sertaç Erman1Abdurrahman Büyükkaya2Mahpeyker Öztürk3,4( )
Department of Engineering Fundamental Sciences, Sakarya University of Applied Sciences, 54050, Sakarya, Türkiye
Department of Mathematics, Karadeniz Technical University, 61080, Trabzon, Türkiye
Department of Mathematics, Faculty of Sciences, Sakarya University, 54050, Sakarya, Türkiye
Picode Software, Education Training Consultancy Research and Development and Trade Co., Ltd., 54050, Sakarya, Türkiye
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Abstract

The present study advances the idea of controlled ( α , c )–interpolative metric spaces as a broader framework that extends interpolative and extended interpolative frameworks and examines their analytical properties in conjunction with Banach-type fixed-point results. The proposed metric structure is then employed to study the fractional-order Chen attractor model defined via the Atangana–Baleanu–Caputo ( A B C ) derivative. Using the newly established metric framework, a suitable fixed-point operator is constructed in the Banach space C ( [ 0 , T ] ; R 3 ), and sufficient contraction conditions ensuring the existence and uniqueness of solutions are derived. The consistency and accuracy of the proposed numerical formulation are demonstrated through simulation results, highlighting improved sensitivity and richer chaotic behavior compared to integer-order models. The obtained results confirm that the controlled interpolative metric approach provides a flexible analytical tool for exploring nonlinear fractional systems and offers new insights into the stability analysis of chaotic dynamical models such as the Chen attractor.

CLC number: 47H10, 54H25

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AIMS Mathematics
Pages 5436-5455

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Cite this article:
Girgin E, Erman S, Büyükkaya A, et al. Analyzing the fractional Chen attractor via controlled interpolative metric contractions. AIMS Mathematics, 2026, 11(3): 5436-5455. https://doi.org/10.3934/math.2026224

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Received: 16 November 2025
Revised: 15 February 2026
Accepted: 25 February 2026
Published: 15 March 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)