Finite-time stability for fractional-order fuzzy neural network with mixed delays and inertial terms
Tiecheng Zhang, Liyan Wang, Yuan Zhang, Jiangtao Deng · AIMS Mathematics · 2024
This paper explored the finite-time stability (FTS) of fractional-order fuzzy inertial neural network with mixed delays. First, the dimension of the model was reduced by the order reduction method. Second, by leveraging the fractional-order finite-time stability theorem, fractional calculus and inequality methods, we established some sufficient conditions to guarantee the FTS of the model under feasible delay-dependent feedback controller and delay-dependent adaptive controller, respectively. Additionally, we derived the settling times (STs) for each control strategy. Finally, we provided two examples to substantiate our findings.