用于非同延迟反应扩散神经网络有限时间同步的新型卡普托分数微分法和混合控制方案

IF 2.7 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Hai Zhang, Chen Wang, Renyu Ye, Jinde Cao
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引用次数: 0

摘要

这项研究的重点是包含卡普托分数偏微分算子和反应扩散项的非相同延迟神经网络(DNN)的有限时间同步(F-TS)。通过构建一个新的卡普托微分不等式,提出了一个新的 F-TS 法则。在应用新的两式和设计两个具有时间延迟和符号函数的混合控制器时,利用菲利波夫微分包容、格林定理和分数拉祖米金定理,推导出了新曼边界条件下引入的卡普托反应扩散非相同 DNN 的 F-TS 准则。这些条件通过代数不等式表示,可以大大减少检查 F-TS 性能的计算量。此外,通过选择不同的阶数、空间位置和扩散参数,说明了 F-TS 结果的有效性和正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Caputo fractional differential approach and hybrid control scheme for finite-time synchronization of nonidentical delayed reaction–diffusion neural networks

This work focuses on the finite-time synchronization (F-TS) for nonidentical delayed neural networks (DNNs) including Caputo fractional partial differential operator and reaction–diffusion terms. A novel F-TS lemma is proposed by constructing a new Caputo differential inequality. Applying the new lemma and designing two hybrid controllers with time delay and the sign function, the F-TS criteria on the introduced Caputo reaction–diffusion nonidentical DNNs under the Neumann boundary condition are derived by making use of the Filippov differential inclusion, Green's theorem, and fractional Razumikhin theorem. The conditions are expressed through the algebraic inequality which can greatly decrease the computation in checking the F-TS performance. Moreover, the validity and correctness of the F-TS results are illustrated by selecting various orders, spatial positions, and diffusion parameters.

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来源期刊
Asian Journal of Control
Asian Journal of Control 工程技术-自动化与控制系统
CiteScore
4.80
自引率
25.00%
发文量
253
审稿时长
7.2 months
期刊介绍: The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.
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