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Main Authors: Alsammani, Abdallah, Farah, Gassan
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2602.07105
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author Alsammani, Abdallah
Farah, Gassan
author_facet Alsammani, Abdallah
Farah, Gassan
contents This paper establishes new sufficient conditions for Mittag-Leffler stability of Caputo fractional-order nonlinear systems with state-dependent delays. The central analytical tool is a class of Lyapunov-Krasovskii functionals that incorporate singular kernels of the form $ξ^{α-1}$ for $α\in (0,1)$, coupling fractional memory effects with delay-induced dynamics in a unified framework. We prove that the resulting stability conditions reduce to computationally tractable linear matrix inequalities and derive explicit formulas for the maximum tolerable delay perturbation. Building on this stability foundation, we design an adaptive controller governed by fractional-order parameter update laws with $σ$-modification and a filter-based delay estimation mechanism that circumvents the need for classical state derivatives, which may not exist for fractional-order trajectories. The convergence analysis establishes ultimate boundedness of the closed-loop system with a computable bound that vanishes as the regularization parameters approach zero. Numerical validation on a three-neuron fractional Hopfield network with state-dependent transmission delays demonstrates that the proposed adaptive scheme reduces cumulative control energy by 99.3\% and achieves an asymptotic state error two orders of magnitude smaller than a comparable fractional sliding mode controller.
format Preprint
id arxiv_https___arxiv_org_abs_2602_07105
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Adaptive Control and Mittag-Leffler Stability of Caputo Fractional Systems with State-Dependent Delays
Alsammani, Abdallah
Farah, Gassan
Dynamical Systems
This paper establishes new sufficient conditions for Mittag-Leffler stability of Caputo fractional-order nonlinear systems with state-dependent delays. The central analytical tool is a class of Lyapunov-Krasovskii functionals that incorporate singular kernels of the form $ξ^{α-1}$ for $α\in (0,1)$, coupling fractional memory effects with delay-induced dynamics in a unified framework. We prove that the resulting stability conditions reduce to computationally tractable linear matrix inequalities and derive explicit formulas for the maximum tolerable delay perturbation. Building on this stability foundation, we design an adaptive controller governed by fractional-order parameter update laws with $σ$-modification and a filter-based delay estimation mechanism that circumvents the need for classical state derivatives, which may not exist for fractional-order trajectories. The convergence analysis establishes ultimate boundedness of the closed-loop system with a computable bound that vanishes as the regularization parameters approach zero. Numerical validation on a three-neuron fractional Hopfield network with state-dependent transmission delays demonstrates that the proposed adaptive scheme reduces cumulative control energy by 99.3\% and achieves an asymptotic state error two orders of magnitude smaller than a comparable fractional sliding mode controller.
title Adaptive Control and Mittag-Leffler Stability of Caputo Fractional Systems with State-Dependent Delays
topic Dynamical Systems
url https://arxiv.org/abs/2602.07105