Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism
This paper is concerned with the nonfragile state estimation for a kind of delayed fractional-order neural network under the event-triggered mechanism (ETM). To reduce the bandwidth occupation of the communication network, the ETM is employed in the sensor-to-estimator channel. Moreover, in order to...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2021/6695353 |
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| _version_ | 1849304550122455040 |
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| author | Xiaoguang Shao Ming Lyu Jie Zhang |
| author_facet | Xiaoguang Shao Ming Lyu Jie Zhang |
| author_sort | Xiaoguang Shao |
| collection | DOAJ |
| description | This paper is concerned with the nonfragile state estimation for a kind of delayed fractional-order neural network under the event-triggered mechanism (ETM). To reduce the bandwidth occupation of the communication network, the ETM is employed in the sensor-to-estimator channel. Moreover, in order to reflect the reality, the transmission delay is taken into account in the model establishment. Sufficient criteria are supplied to make sure that the augmented system is asymptotically stable by using the fractional-order Lyapunov indirect approach and the linear matrix inequality method. In the end, the theoretical result is shown by means of two numerical examples. |
| format | Article |
| id | doaj-art-3bf4b3a8461e4cbdbf80a499095252fb |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-3bf4b3a8461e4cbdbf80a499095252fb2025-08-20T03:55:41ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2021-01-01202110.1155/2021/66953536695353Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered MechanismXiaoguang Shao0Ming Lyu1Jie Zhang2School of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaThis paper is concerned with the nonfragile state estimation for a kind of delayed fractional-order neural network under the event-triggered mechanism (ETM). To reduce the bandwidth occupation of the communication network, the ETM is employed in the sensor-to-estimator channel. Moreover, in order to reflect the reality, the transmission delay is taken into account in the model establishment. Sufficient criteria are supplied to make sure that the augmented system is asymptotically stable by using the fractional-order Lyapunov indirect approach and the linear matrix inequality method. In the end, the theoretical result is shown by means of two numerical examples.http://dx.doi.org/10.1155/2021/6695353 |
| spellingShingle | Xiaoguang Shao Ming Lyu Jie Zhang Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism Discrete Dynamics in Nature and Society |
| title | Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism |
| title_full | Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism |
| title_fullStr | Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism |
| title_full_unstemmed | Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism |
| title_short | Nonfragile Estimator Design for Fractional-Order Neural Networks under Event-Triggered Mechanism |
| title_sort | nonfragile estimator design for fractional order neural networks under event triggered mechanism |
| url | http://dx.doi.org/10.1155/2021/6695353 |
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