Fixed-time stabilization of fuzzy neutral-type inertial neural networks with time-varying delay

被引:41
作者
Aouiti, Chaouki [1 ,2 ]
Hui, Qing [3 ]
Jallouli, Hediene [1 ,2 ]
Moulay, Emmanuel [3 ,4 ]
机构
[1] Univ Carthage, Fac Sci Bizerta, Dept Math, Res Unit Math, UR13ES47,BP W, Zarzouna 7021, Bizerta, Tunisia
[2] Univ Carthage, Fac Sci Bizerta, Dept Math, Res Unit Applicat, UR13ES47,BP W, Zarzouna 7021, Bizerta, Tunisia
[3] Univ Nebraska, Dept Elect & Comp Engn, Lincoln, NE 68588 USA
[4] Univ Poitiers, XLIM UMR CNRS 7252, 11 Bd Marie & Pierre Curie, F-86073 Poitiers 9, France
关键词
Inertial neural networks; Fuzzy neural networks; Time-varying delay; Fixed-time stability; FINITE-TIME; EXPONENTIAL STABILITY; SYNCHRONIZATION;
D O I
10.1016/j.fss.2020.10.018
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper addresses the problem of fixed-time stabilization for a class of fuzzy neutral-type inertial neural networks (FNTINNs) with time-varying delay. By using a novel fixed-time stability theorem for dynamical systems, two different feedback control laws are designed to ensure the fixed-time stabilization of FNTINNs with time-varying delay. The proposed theoretical results can lead to a better upper settling-time estimation compared to existing results. Finally, three simulation examples are provided to illustrate the validity of the proposed theoretical results. ? 2020 Elsevier B.V. All rights reserved. This paper addresses the problem of fixed-time stabilization for a class of fuzzy neutral-type inertial neural networks (FNTINNs) with time-varying delay. By using a novel fixed-time stability theorem for dynamical systems, two different feedback control laws are designed to ensure the fixed-time stabilization of FNTINNs with time-varying delay. The proposed theoretical results can lead to a better upper settling-time estimation compared to existing results. Finally, three simulation examples are provided to illustrate the validity of the proposed theoretical results.
引用
收藏
页码:48 / 67
页数:20
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