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A Model-Free Finite-Time Control Technique for Synchronization of Variable-Order Fractional Hopfield-like Neural Network.
- Source :
-
Fractal & Fractional . May2023, Vol. 7 Issue 5, p349. 14p. - Publication Year :
- 2023
-
Abstract
- Although the literature presents promising techniques for the control of integer-order systems, control and synchronizing fractional systems still need further improvement to ensure their robustness and convergence time. This study aims to address this issue by proposing a model-free and finite-time super-twisting control technique for a variable-order fractional Hopfield-like neural network. The proposed controller is enhanced with an intelligent observer to account for disturbances and uncertainties in the chaotic model of the Hopfield-like neural network. The controller is able to regulate the system even when its complex variable-order fractional dynamic is completely unknown. Moreover, the proposed technique guarantees finite-time convergence of the closed-loop system. First, the dynamics of the variable-order fractional Hopfield-like neural network are examined. Then, the control design is described and its finite-time stability is proven. The controller is then applied to the variable-order fractional system and tested under two different scenarios to evaluate its performance. The results of the simulations demonstrate the excellent performance of the proposed method in both scenarios. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25043110
- Volume :
- 7
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Fractal & Fractional
- Publication Type :
- Academic Journal
- Accession number :
- 163968429
- Full Text :
- https://doi.org/10.3390/fractalfract7050349