Extended Robust Exponential Stability of Fuzzy Switched Memristive Inertial Neural Networks With Time-Varying Delays on Mode-Dependent Destabilizing Impulsive Control Protocol
This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The memristive model presented here is treated as a switched system rather than e...
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| Published in: | IEEE transaction on neural networks and learning systems Vol. 32; no. 1; pp. 308 - 321 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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United States
IEEE
01-01-2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The memristive model presented here is treated as a switched system rather than employing the theory of differential inclusion and set-value map. To optimize the robust exponentially stable process and reduce the cost of time, hybrid mode-dependent destabilizing impulsive and adaptive feedback controllers are simultaneously applied to stabilize FSMINNs. In the new model, the multiple impulsive effects exist between two switched modes, and the multiple switched effects may also occur between two impulsive instants. Based on switched analysis techniques, the Takagi-Sugeno (T-S) fuzzy method, and the average dwell time, extended robust exponential stability conditions are derived. Finally, simulation is provided to illustrate the effectiveness of the results. |
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| AbstractList | This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The memristive model presented here is treated as a switched system rather than employing the theory of differential inclusion and set-value map. To optimize the robust exponentially stable process and reduce the cost of time, hybrid mode-dependent destabilizing impulsive and adaptive feedback controllers are simultaneously applied to stabilize FSMINNs. In the new model, the multiple impulsive effects exist between two switched modes, and the multiple switched effects may also occur between two impulsive instants. Based on switched analysis techniques, the Takagi–Sugeno (T-S) fuzzy method, and the average dwell time, extended robust exponential stability conditions are derived. Finally, simulation is provided to illustrate the effectiveness of the results. |
| Author | Wang, Xiangxiang Yang, Nijing Zhong, Shouming Yu, Yongbin Tashi, Nyima |
| Author_xml | – sequence: 1 givenname: Yongbin orcidid: 0000-0001-6022-7504 surname: Yu fullname: Yu, Yongbin email: ybyu@uestc.edu.cn organization: School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China – sequence: 2 givenname: Xiangxiang orcidid: 0000-0001-9341-1068 surname: Wang fullname: Wang, Xiangxiang organization: School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China – sequence: 3 givenname: Shouming orcidid: 0000-0002-0334-6117 surname: Zhong fullname: Zhong, Shouming email: zhongsm@uestc.edu.cn organization: School of Mathematical Science, University of Electronic Science and Technology of China, Chengdu, China – sequence: 4 givenname: Nijing orcidid: 0000-0001-5553-0031 surname: Yang fullname: Yang, Nijing organization: School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China – sequence: 5 givenname: Nyima surname: Tashi fullname: Tashi, Nyima email: nmzx@tibet.edu.cn organization: School of Information Science and Technology, Tibet University, Lhasa, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32217485$$D View this record in MEDLINE/PubMed |
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| Snippet | This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays... |
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| SubjectTerms | Algorithms Artificial neural networks Computer Simulation Control stability Control theory Delays Dwell time Extended robust exponential stability Feedback Feedback control fuzzy Fuzzy Logic impulsive effects memristive inertial neural networks Memristors mode dependent Models, Theoretical Neural networks Neural Networks, Computer Robustness (mathematics) Stability analysis switched Switches Time varying control |
| Title | Extended Robust Exponential Stability of Fuzzy Switched Memristive Inertial Neural Networks With Time-Varying Delays on Mode-Dependent Destabilizing Impulsive Control Protocol |
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