Fixed/Prescribed-Time Synchronization of Fuzzy Inertial Memristive Neural Networks With Time-Varying Delay: Interval Matrix Method and PI Control
This paper investigates the fixed/prescribed-time synchronization issues for fuzzy inertial memristive neural networks (FIMNNs) with time-varying delay, which integrate fuzzy logic, inertial terms, memristors, and time-varying delays simultaneously. The interval matrix method is employed firstly to...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10965618/ |
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| Summary: | This paper investigates the fixed/prescribed-time synchronization issues for fuzzy inertial memristive neural networks (FIMNNs) with time-varying delay, which integrate fuzzy logic, inertial terms, memristors, and time-varying delays simultaneously. The interval matrix method is employed firstly to deal with the state-dependent switching parameters, which is distinguished from the existing maximum absolute value approach. Consequently, the FIMNNs with time-varying delay are transformed into a type of delayed fuzzy systems, with coefficients characterized by a series of interval matrices. Following this, within the framework of Filippov solutions and differential inclusions, fixed/prescribed-time synchronization is comprehensively discussed. Two novel PI feedback controllers are synthesized through the resolution of a series of linear matrix inequalities (LMIs), followed by numerical simulations to demonstrate their effectiveness. |
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| ISSN: | 2169-3536 |