The Synchronization of Hyperchaotic Systems Using a Novel Interval Type-2 Fuzzy Neural Network Controller

被引：7
|
作者：
Tien-Loc Le [1 ]
Van-Binh Ngo [1 ]
机构：
[1] Lac Hong Univ, Fac Mechatron & Elect, Bien Hoa 810000, Dong Nai, Vietnam
来源：
IEEE ACCESS | 2022年 / 10卷
关键词：
Synchronization; Fuzzy logic; Uncertainty; Fuzzy neural networks; Fuzzy control; Optimization; Heuristic algorithms; 5-D hyperchaotic systems; fuzzy neural network; type-2 fuzzy system; 3DGMFs; Jaya algorithm; ROBUST SYNCHRONIZATION; CHAOTIC SYSTEMS; LOGIC SYSTEMS; ALGORITHM; DESIGN;
D O I：
10.1109/ACCESS.2022.3211515
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposed a novel interval type-2 fuzzy neural network controller (NT2FC) to synchronize 5-D hyperchaotic systems with noise disturbance and system uncertainties. In the proposed controller, the type 2 fuzzy set is designed with the 3-dimensional Gaussian membership functions (3DGMFs) to increase the system's ability to respond to uncertainty. The parameters of the NT2FC controller are updated online via adaptation laws, which are built based on the gradient descent approach. The system stability is ensured through the Lyapunov stability analysis. In addition, the modified Jaya algorithm (MJA) is applied to optimize the learning rates in adaptation laws. Finally, the efficiency of the proposed NT2FC is examined by the numerical simulation of the hyperchaotic system's synchronization.
引用
收藏
页码：105966 / 105982
页数：17
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