Control Strategies for Mittag-Leffler Synchronization in Variable-Order Fractional FitzHugh-Nagumo Reaction-Diffusion Networks

This work presents a synchronization control methodology for Variable Fractional-Order Reaction-Diffusion systems (VFO-RDs), focusing on the FitzHugh-Nagumo model. Using Caputo fractional difference operators with time-dependent orders, we design both linear and nonlinear controllers and prove Mittag-Leffler synchronization under explicit constraints. Key contributions: (i) a unified Mittag-Leffler Synchronization (MLSY) framework for variableorder systems using linear and nonlinear controllers; (ii) integration of absolute-state feedback with Lyapunov-based stability for robustness and fast convergence; (iii) demonstration on the FitzHugh-Nagumo (FHN) model, indicating broader applicability in neural engineering.

Authors

Institutions

Publication Details

Journal
Contemporary Mathematics
Published
2025-09-16
DOI
https://doi.org/10.37256/cm.6520257613
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Control Strategies for Mittag-Leffler Synchronization in Variable-Order Fractional FitzHugh-Nagumo Reaction-Diffusion Networks

Anjan Biswas, Iqbal M. Batiha, Shaher Momani, Iqbal H. Jebril
Contemporary Mathematics
Nonlinear Dynamics and Pattern Formation
article

Control Strategies for Mittag-Leffler Synchronization in Variable-Order Fractional FitzHugh-Nagumo Reaction-Diffusion Networks

Anjan Biswas, Iqbal M. Batiha, Shaher Momani, Iqbal H. Jebril
article en

Abstract

This work presents a synchronization control methodology for Variable Fractional-Order Reaction-Diffusion systems (VFO-RDs), focusing on the FitzHugh-Nagumo model. Using Caputo fractional difference operators with time-dependent orders, we design both linear and nonlinear controllers and prove Mittag-Leffler synchronization under explicit constraints. Key contributions: (i) a unified Mittag-Leffler Synchronization (MLSY) framework for variableorder systems using linear and nonlinear controllers; (ii) integration of absolute-state feedback with Lyapunov-based stability for robustness and fast convergence; (iii) demonstration on the FitzHugh-Nagumo (FHN) model, indicating broader applicability in neural engineering.

Contemporary Mathematics
Al-Zaytoonah University of Jordan (JO), Grambling State University (US), Ajman University (AE)
Openalex Percentile: Top 71%
Nonlinear Dynamics and Pattern Formation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.