Finite-Time Passivity for Coupled Fractional-Order Neural Networks With Multistate or Multiderivative Couplings

被引:16
作者
Liu, Chen-Guang [1 ]
Wang, Jin-Liang [2 ,3 ]
Wu, Huai-Ning [4 ,5 ]
机构
[1] Tiangong Univ, Sch Comp Sci & Technol, Tianjin 300387, Peoples R China
[2] Tiangong Univ, Sch Comp Sci & Technol, Tianjin Key Lab Autonomous Intelligence Technol &, Tianjin 300387, Peoples R China
[3] Linyi Univ, Sch Informat Sci & Technol, Linyi 276005, Shandong, Peoples R China
[4] Beihang Univ, Sch Automat Sci & Elect Engn, Sci & Technol Aircraft Control Lab, Beijing 100191, Peoples R China
[5] Peng Cheng Lab, Shenzhen 518000, Peoples R China
基金
中国国家自然科学基金;
关键词
Couplings; Synchronization; Neural networks; Adaptive systems; Symmetric matrices; Stability criteria; Numerical stability; Coupled fractional-order neural networks (CFNNs); finite-time passivity (FTP); multiderivative couplings; multistate couplings; STABILITY ANALYSIS; STABILIZATION;
D O I
10.1109/TNNLS.2021.3132069
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article mainly delves into the finite-time passivity (FTP) for coupled fractional-order neural networks with multistate couplings (CFNNMSCs) or coupled fractional-order neural networks with multiderivative couplings (CFNNMDCs). Distinguishing from the traditional FTP definitions, several concepts of FTP for fractional-order systems are given. On one hand, we present several sufficient conditions to ensure the FTP for CFNNMSCs by artfully designing a state-feedback controller and an adaptive state-feedback controller. On the other hand, by utilizing some inequality techniques, two sets of FTP criteria for CFNNMDCs are also established on the basis of the state-feedback and adaptive state-feedback controllers. Finally, numerical examples are used to demonstrate the validity of the derived FTP criteria.
引用
收藏
页码:5976 / 5987
页数:12
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