Finite-Time Mixed H∞/Passivity for Neural Networks With Mixed Interval Time-Varying Delays Using the Multiple Integral Lyapunov-Krasovskii Functional

• Published in: IEEE access Vol. 9; pp. 89461 - 89475
• Main Authors: Phanlert, Chalida, Botmart, Thongchai, Weera, Wajaree, Junsawang, Prem
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">H ∞ and passivity; Criteria; Delays; Derivatives; finite-time bounded; Inequality; Integral equations; Integrals; Linear matrix inequalities; Lyapunov-Krasovskii function; Mathematical analysis; Neural networks; Numerical stability; Passivity; Stability criteria; Symmetric matrices; time-varying delays
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3089374

In this article, we consider the finite-time mixed <inline-formula> <tex-math notation="LaTeX">H_{\infty } </tex-math></inline-formula>/passivity, finite-time stability, and finite-time boundedness for generalized neural networks with interval distributed and discrete time-varying delays. It is noted that this is the first time for studying in the combination of <inline-formula> <tex-math notation="LaTeX">H_{\infty } </tex-math></inline-formula>, passivity, and finite-time boundedness. To obtain several sufficient criteria achieved in the form of linear matrix inequalities (LMIs), we introduce an appropriate Lyapunov-Krasovskii function (LKF) including single, double, triple, and quadruple integral terms, and estimating the bound of time derivative in LKF with the use of Jensen's integral inequality, an extended single and double Wirtinger's integral inequality, and a new triple integral inequality. These LMIs can be solved by using MATLAB's LMI toolbox. Finally, five numerical simulations are shown to illustrate the effectiveness of the obtained results. The received criteria and published literature are compared.