Modeling, Optimization, and Control of Fractional-Order Neural Networks and Nonlinear Systems, Second Edition

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".

Deadline for manuscript submissions: 17 October 2026 | Viewed by 614

Special Issue Editors


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Guest Editor
School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu 610065, China
Interests: fractional-order neural networks; nonlinear systems; networked control systems; control theory and application of neural network
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Guest Editor
School of Cyber Science and Engineering, Sichuan University, Chengdu 610065, China
Interests: fractional-order sliding mode control, information physical systems; DoS attacks; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China
Interests: fractional-order systems; industrial control systems; network control systems; cyber–physical systems; optimal control; network security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the increasing application of fractional-order theory in the fields of neural networks and nonlinear systems, this Special Issue, titled “Modeling, Optimization, and Control of Fractional-Order Neural Networks and Nonlinear Systems, Second Edition”, aims to provide a platform for researchers to showcase their latest research findings, innovative methods and application cases in this field.

The purpose of launching this Special Issue is to bring together significant developments concerning the modeling, optimization and control of fractional-order neural networks and nonlinear systems, and facilitate research collaboration and the exchange of ideas surrounding this topic. Potential topics include, but are not limited to, the following:

  • Modeling and analysis of fractional-order neural networks;
  • Reinforcement learning control and optimization of fractional-order neural networks;
  • Intelligent learning and adaptive control of fractional-order neural networks;
  • Robust distributed control methods of nonlinear systems;
  • Sampled-data and event-triggered intelligent control;
  • Distributed intelligent control and optimization applications;
  • Security control of networked control systems.

Prof. Dr. Kaibo Shi
Dr. Zhinan Peng
Prof. Dr. Xin Wang
Dr. Xiao Cai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fractal and Fractional is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fractional order neural networks
  • nonlinear systems
  • networked control systems
  • modelling and analysis
  • control and optimization
  • intelligent learning
  • multiagent systems

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Published Papers (1 paper)

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Research

16 pages, 528 KB  
Article
A Novel Approach to the Dynamics of a Fractional-Order Neural Networks with Delay Through Two-Point Self-Mapped Contraction
by Sumati Kumari Panda, Nalleboyina Vijaya, Amer Hassan Albargi and Jamshaid Ahmad
Fractal Fract. 2026, 10(1), 39; https://doi.org/10.3390/fractalfract10010039 - 8 Jan 2026
Viewed by 397
Abstract
The paper explores the uniform stability and equilibrium characteristics of a class of neural networks of fractional order with time delay. The two-point self-mapped contraction theorem is used in order to establish sufficient conditions for the uniform stability of the system. Further, the [...] Read more.
The paper explores the uniform stability and equilibrium characteristics of a class of neural networks of fractional order with time delay. The two-point self-mapped contraction theorem is used in order to establish sufficient conditions for the uniform stability of the system. Further, the existence, uniqueness, and uniform stability of the equilibrium point are established. A set of numerical examples is presented to proclaim the validity and usefulness of the proposed results. Full article
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