Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations
This paper deals with the finite-time synchronization problem of a class of fuzzy neural networks with hybrid delays and uncertain nonlinear perturbations. By applying the famous finite-time stability theory, combining differential inequality techniques, and the analysis approach, several new algebr...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2022/1448819 |
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| _version_ | 1832548820354859008 |
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| author | Shuyue Zhao Kelin Li Weiyi Hu |
| author_facet | Shuyue Zhao Kelin Li Weiyi Hu |
| author_sort | Shuyue Zhao |
| collection | DOAJ |
| description | This paper deals with the finite-time synchronization problem of a class of fuzzy neural networks with hybrid delays and uncertain nonlinear perturbations. By applying the famous finite-time stability theory, combining differential inequality techniques, and the analysis approach, several new algebraic sufficient criteria are obtained to realize finite-time synchronization between the drive system and the response system by designing a state feedback controller and an adaptive controller. Taking discrete delays, distributed delays, and uncertain nonlinear perturbations into account in fuzzy cellular neural networks makes the neural system more general than most existing cellular neural networks. Two different novel types of controllers designed to achieve finite-time synchronization can not only effectively overcome the influence of time delays and perturbations but also change their form according to the change of system state or perturbation to achieve a better control effect. Meanwhile, some algebraic sufficient criteria obtained in this paper can be proved by the parameters of the system itself, and the complex calculation of matrix inequality is avoided. Finally, the validity of our proposed results is confirmed by several examples and simulations. Furthermore, a secure communication problem is presented to further illustrate the fact of the obtained results. |
| format | Article |
| id | doaj-art-63c799d7ecdc4b0d9cad97f4b5dd3ebb |
| institution | Kabale University |
| issn | 1687-711X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-63c799d7ecdc4b0d9cad97f4b5dd3ebb2025-02-03T06:12:57ZengWileyAdvances in Fuzzy Systems1687-711X2022-01-01202210.1155/2022/1448819Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear PerturbationsShuyue Zhao0Kelin Li1Weiyi Hu2School of Mathematics and StatisticsSchool of Mathematics and StatisticsSchool of Mathematics and StatisticsThis paper deals with the finite-time synchronization problem of a class of fuzzy neural networks with hybrid delays and uncertain nonlinear perturbations. By applying the famous finite-time stability theory, combining differential inequality techniques, and the analysis approach, several new algebraic sufficient criteria are obtained to realize finite-time synchronization between the drive system and the response system by designing a state feedback controller and an adaptive controller. Taking discrete delays, distributed delays, and uncertain nonlinear perturbations into account in fuzzy cellular neural networks makes the neural system more general than most existing cellular neural networks. Two different novel types of controllers designed to achieve finite-time synchronization can not only effectively overcome the influence of time delays and perturbations but also change their form according to the change of system state or perturbation to achieve a better control effect. Meanwhile, some algebraic sufficient criteria obtained in this paper can be proved by the parameters of the system itself, and the complex calculation of matrix inequality is avoided. Finally, the validity of our proposed results is confirmed by several examples and simulations. Furthermore, a secure communication problem is presented to further illustrate the fact of the obtained results.http://dx.doi.org/10.1155/2022/1448819 |
| spellingShingle | Shuyue Zhao Kelin Li Weiyi Hu Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations Advances in Fuzzy Systems |
| title | Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations |
| title_full | Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations |
| title_fullStr | Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations |
| title_full_unstemmed | Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations |
| title_short | Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations |
| title_sort | synchronization in finite time of fuzzy neural networks with hybrid delays and uncertain nonlinear perturbations |
| url | http://dx.doi.org/10.1155/2022/1448819 |
| work_keys_str_mv | AT shuyuezhao synchronizationinfinitetimeoffuzzyneuralnetworkswithhybriddelaysanduncertainnonlinearperturbations AT kelinli synchronizationinfinitetimeoffuzzyneuralnetworkswithhybriddelaysanduncertainnonlinearperturbations AT weiyihu synchronizationinfinitetimeoffuzzyneuralnetworkswithhybriddelaysanduncertainnonlinearperturbations |