Robust resilient H_∞ performance for finite‐time boundedness of neutral‐type neural networks with time‐varying delays

Abstract

This paper discusses the resilient H ∞ performance for finite-time boundedness of neutral-type neural networks with time-varying delays. The presented theoretical analysis allows establishing the finite-time bounded of the real response of a delayed neural networks. In addition, we propose finite-time stability conditions with time-varying delay. By choosing an appropriate Lyapunov-Krasovskii functional, and employing an auxiliary function-based integral inequality and Wirtinger's based integral inequality, the sufficient criteria are derived in terms of linear matrix inequalities. The purpose is to design the system is not only finite-time bounded with a specified decay rate but also satisfies an H ∞ performance requirement. Theoretical results are tested through a numerical example.

Real‐time model‐free resilient control for discrete nonlinear systems

“…In Mardani et al [9], a nonfragile controller design of uncertain saturated polynomial fuzzy systems is described, which is subjected to persistent bounded disturbance with experimental results applied to a ball-and-beam system in continuous time. Shanmugam et al [10] propose a robust resilient H∞ performance for finite-time boundedness of neutral-type neural networks with time-varying delays in continuous time. From the previous works, it is clear that modern control systems should be robust to adverse events yet also exhibit quick recovery from degraded performance.…”