Recursive filtering for nonlinear systems, one of the core technologies of modern industrial
systems, is an ever-increasing research topic from the control and computer communities …

This article investigates a neural network (NN)‐based control problem for unknown discrete‐
time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event …

This study deals with the problem of the H∞ state estimation for discrete-time memristive
neural networks with time-varying delays, where the output is subject to randomly occurring …

In industrial systems, the multi-rate sampling strategy has been widely used due to the
advantage in balancing cost and performance as well as the psychical characteristics of the …

In this article, the chance-constrained state estimation problem is investigated for a class of
time-varying neural networks subject to measurements degradation and randomly occurring …

This article focuses on the distributed maximum correntropy filtering issue for general
stochastic nonlinear systems subject to deception attacks. The considered nonlinear …

This article presents an event‐triggered approach to security control for networked systems
by using hybrid attack model. Stochastic deception attacks, replay attacks, and denial of …

In this paper, a new filtering fusion problem is studied for nonlinear cyber-physical systems
under error-variance constraints and denial-of-service attacks. To prevent data collision and …

In this paper, the distributed state estimation problem is studied for renewable energy
microgrids with sensor saturations. A system model for the microgrids with sensor …

This paper studies the sampled-data resilient control for stochastic nonlinear cyber-physical
systems (CPSs) under denial-of-service (DoS) attacks. First, under the sampled-data control …