Passive decomposition and gradient control of fractional-order nonlinear systems

Fernández‐Anaya, Guillermo; Martínez-Fuentes, Óscar; Muñoz‐Vázquez, Aldo Jonathan; Sánchez‐Torres, Juan Diego; Quezada-Téllez, Luis Alberto; Meléndez‐Vázquez, Fidel

doi:10.1007/s11071-022-07531-2

Nonlinear Dyn

2022

DOI: 10.1007/s11071-022-07531-2

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Passive decomposition and gradient control of fractional-order nonlinear systems

Guillermo Fernández‐Anaya

Óscar Martínez-Fuentes

Aldo Jonathan Muñoz‐Vázquez

et al.

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2024

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Finite-time and global Mittag-Leffler stability of fractional-order neural networks with S-type distributed delays

Liu,

Zuo,

2024

MATH

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<abstract><p>This paper was mainly concerned with the stability analysis of a class of fractional-order neural networks with S-type distributed delays. By using the properties of Riemann-Liouville fractional-order derivatives and integrals, along with the additivity of integration intervals and initial conditions, fractional-order integrals of the state function with S-type distributed delays were transformed into fractional-order integrals of the state function without S-type distributed delays. By virtue of the theory of contractive mapping and the Bellman-Gronwall inequality, the sufficient conditions for finite-time stability and global Mittag-Leffler stability were obtained when certain conditions were satisfied. Moreover, the correctness and realizability of the conclusion were verified through the presentation of two illustrative numerical simulation examples.</p></abstract>

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Finite-time and global Mittag-Leffler stability of fractional-order neural networks with S-type distributed delays

Liu,

Zuo,

2024

MATH

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Passive decomposition and gradient control of fractional-order nonlinear systems

Cited by 1 publication

References 41 publications

Finite-time and global Mittag-Leffler stability of fractional-order neural networks with S-type distributed delays

Finite-time and global Mittag-Leffler stability of fractional-order neural networks with S-type distributed delays

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