Multi-sensor filtering fusion (MSFF) is a fascinating subject in the realm of networked filtering
due to its advantage of effectively integrating sensor outputs from multiple sources. Owing to …

Abstract Model-based methods are widely used for the fault diagnosis of stochastic dynamic
systems by simply using the input–output relationship of the system. Despite encouraging …

In this paper, we investigate the distributed recursive fault estimation problem for a class of
discrete time-varying systems with binary encoding schemes over a sensor network. The …

This article is concerned with the partial-node-based (PNB) state estimation problem for
delayed complex networks (DCNs) subject to intermittent measurement outliers (IMOs). In …

This article addresses the state estimation problem for a class of nonlinear complex
networks (CNs) under attack. First, a novel important‐data‐based (IDB) attack strategy is …

In this letter, the recursive fault estimation issue is considered for nonlinear time-varying
systems subject to the effects induced by energy harvesting sensors and uniform …

In this paper, the joint state and fault estimation problem is investigated for a class of discrete-
time complex networks with measurement saturations and stochastic nonlinearities. The …

Recently, deep learning techniques have been widely applied to fault diagnosis due to their
outstanding feature extraction abilities. The success of deep-learning-based fault diagnosis …

This paper investigates the full states-constrained resilient control for vehicle platoon
systems with false data injection (FDI) attack, and actuator fault. A cyber-physical notion …

This paper focuses on the distributed filtering and fault estimation problems for a class of
complex networks, where the communications between filters at different nodes are subject …