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Observer-Based Dissipativity Control for T–S Fuzzy Neural Networks With Distributed Time-Varying Delays.
- Source :
- IEEE Transactions on Cybernetics; Nov2021, Vol. 51 Issue 11, p5248-5258, 11p
- Publication Year :
- 2021
-
Abstract
- An observer-based dissipativity control for Takagi–Sugeno (T–S) fuzzy neural networks with distributed time-varying delays is studied in this article. First, the network channel delays are modeled as a distributed delay with its kernel. To make full use of kernels of the distributed delay, a Lyapunov–Krasovskii functional (LKF) is established with the kernel of the distributed delay. It is noted that the novel LKF and delay-dependent reciprocally convex inequality plays an important role in dealing with global asymptotical stability and strict $(\mathcal{Q}, \mathcal{S},\mathcal{R})$ - $\alpha $ -dissipativity of the T–S fuzzy delayed model. Through the constructed LKF, a new set of less conservative linear matrix inequality (LMI) conditions is presented to obtain an observer-based controller for the T–S fuzzy delayed model. This proposed observer-based controller ensures that the state of the closed-loop system is globally asymptotically stable and strictly $(\mathcal{Q}, \mathcal{S},\mathcal{R})$ - $\alpha $ -dissipative. Finally, the effectiveness of the proposed results is shown in numerical simulations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21682267
- Volume :
- 51
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Cybernetics
- Publication Type :
- Academic Journal
- Accession number :
- 153789609
- Full Text :
- https://doi.org/10.1109/TCYB.2020.2977682