Sliding Mode Stabilization of Memristive Neural Networks With Leakage Delays and Control Disturbance

被引:11
|
作者
Sun, Bo [1 ]
Cao, Yuting [2 ]
Guo, Zhenyuan [2 ]
Yan, Zheng [3 ]
Wen, Shiping [1 ]
Huang, Tingwen [4 ]
Chen, Yiran [5 ]
机构
[1] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Peoples R China
[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
[3] Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
[4] Texas A&M Univ Qatar, Sci Program, Doha, Qatar
[5] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
关键词
Delays; Biological neural networks; Memristors; Immune system; Neurons; Time-varying systems; Control disturbance; leakage delay; memristive neural network (MNN); sliding mode control (SMC); stability; time-varying delay; STABILITY ANALYSIS; SYNCHRONIZATION; PASSIVITY; SYSTEMS;
D O I
10.1109/TNNLS.2020.2984000
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this article, we investigate a class of memristive neural networks (MNNs) with time-varying delays and leakage delays via sliding mode control (SMC) with and without control disturbance. SMC is used to ensure MNNs' stability. According to the characteristics of the MNNs, we consider the following three models: the first is the MNNs with time-varying delays, the second is the MNNs with time-varying delays and the control disturbance, and the third is the MNNs with time-varying delays, leakage delays, and the control disturbance. We quote some assumptions and lemmas to ensure that our main results are true. The sliding surface, the corresponding sliding mode controller, and the Lyapunov functions are constructed in different models to ensure MNNs' stability. Finally, some examples and simulations verify the validity of our main results by solving linear matrix inequality (LMI), and the conclusions and analysis of the results are given.
引用
收藏
页码:1254 / 1263
页数:10
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