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Finite-Time Synchronization of Fractional-Order Delayed Fuzzy Cellular Neural Networks With Parameter Uncertainties
The finite-time synchronization (FTS) is studied for a class of fractional-order delayed fuzzy cellular neural networks (FODFCNNs) with parameter uncertainties. A linear fractional-order finite time inequality (FOFTI) [Formula Omitted] is extended to the nonlinear case [Formula Omitted], [Formula Om...
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Published in: | IEEE transactions on fuzzy systems 2023-06, Vol.31 (6), p.1769-1779 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The finite-time synchronization (FTS) is studied for a class of fractional-order delayed fuzzy cellular neural networks (FODFCNNs) with parameter uncertainties. A linear fractional-order finite time inequality (FOFTI) [Formula Omitted] is extended to the nonlinear case [Formula Omitted], [Formula Omitted], which plays a vital role in the FTS of fractional-order systems. However, for the case of [Formula Omitted], a theoretical cornerstone justifying its use is still missing. To fill this research gap, on the basis of the [Formula Omitted] inequality and the rule for fractional-order derivative of composite function, a nonlinear FOFTI [Formula Omitted], [Formula Omitted] is developed. Furthermore, a nonlinear FOFTI [Formula Omitted] is also established. These two novel inequalities provide the new tools for the research on the finite time stability and synchronization of fractional-order systems and can greatly extend the pioneer ones. Next, on the basis of these novel inequalities, the feedback controller is designed and two novel FTS criteria of FODFCNNs with parameter uncertainties are obtained. Finally, two examples are presented to verify the effectiveness of the derived results. |
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ISSN: | 1063-6706 1941-0034 |
DOI: | 10.1109/TFUZZ.2022.3214070 |