Asymptotic stability of delayed fractional-order fuzzy neural networks with impulse effects. (English) Zbl 1398.93293
Summary: In this paper, we investigate the asymptotic stability of fractional-order fuzzy neural networks with fixed-time impulse and time delay. According to the fractional Barbalat’s lemma, Riemann-Liouville operator and Lyapunov stability theorem, some sufficient conditions are obtained to ensure the asymptotic stability of the fractional-order fuzzy neural networks. Two numerical examples are also given to illustrate the feasibility and effectiveness of the obtained results.
MSC:
| 93D20 | Asymptotic stability in control theory |
| 68T05 | Learning and adaptive systems in artificial intelligence |
| 93C42 | Fuzzy control/observation systems |
| 26A33 | Fractional derivatives and integrals |
| 34A08 | Fractional ordinary differential equations |
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