Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems
Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing...
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| Format: | Article |
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MDPI AG
2018-12-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/19/1/74 |
| _version_ | 1818000357171658752 |
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| author | Dechao Chen Shuai Li Qing Wu |
| author_facet | Dechao Chen Shuai Li Qing Wu |
| author_sort | Dechao Chen |
| collection | DOAJ |
| description | Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach inherently possesses the advantage of super-exponential convergence property, which makes the synchronization process faster and more accurate. Theoretical analyses on the stability and convergence advantages in terms of both faster convergence speed and lower error bound within the task duration are rigorously presented. Moreover, three synchronization examples substantiate the validity of the SEZN approach and the related controller for synchronization of chaotic sensor systems. Comparisons with other approaches such as the CZN approach, show the convergence superiority of the proposed SEZN approach. Finally, extensive tests further investigate the impact on convergence performance by choosing different values of design parameter and initial state. |
| first_indexed | 2024-04-14T03:21:39Z |
| format | Article |
| id | doaj.art-38790b501c3f49bba38dd256fb00267f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:21:39Z |
| publishDate | 2018-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-38790b501c3f49bba38dd256fb00267f2022-12-22T02:15:18ZengMDPI AGSensors1424-82202018-12-011917410.3390/s19010074s19010074Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor SystemsDechao Chen0Shuai Li1Qing Wu2School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaDepartment of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, ChinaSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, ChinaDue to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach inherently possesses the advantage of super-exponential convergence property, which makes the synchronization process faster and more accurate. Theoretical analyses on the stability and convergence advantages in terms of both faster convergence speed and lower error bound within the task duration are rigorously presented. Moreover, three synchronization examples substantiate the validity of the SEZN approach and the related controller for synchronization of chaotic sensor systems. Comparisons with other approaches such as the CZN approach, show the convergence superiority of the proposed SEZN approach. Finally, extensive tests further investigate the impact on convergence performance by choosing different values of design parameter and initial state.http://www.mdpi.com/1424-8220/19/1/74zeroing neurodynamicrecurrent neural networkschaossensorschaotic disturbance rejectionfast synchronization |
| spellingShingle | Dechao Chen Shuai Li Qing Wu Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems Sensors zeroing neurodynamic recurrent neural networks chaos sensors chaotic disturbance rejection fast synchronization |
| title | Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems |
| title_full | Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems |
| title_fullStr | Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems |
| title_full_unstemmed | Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems |
| title_short | Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems |
| title_sort | rejecting chaotic disturbances using a super exponential zeroing neurodynamic approach for synchronization of chaotic sensor systems |
| topic | zeroing neurodynamic recurrent neural networks chaos sensors chaotic disturbance rejection fast synchronization |
| url | http://www.mdpi.com/1424-8220/19/1/74 |
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