Industrial cyber-physical systems (CPSs) are large-scale, geographically dispersed, and life-
critical systems, in which lots of sensors and actuators are embedded and networked …

This article is concerned with the distributed recursive filtering of cyber-physical systems
consisting of a set of spatially distributed subsystems. Due to the vulnerability of …

Demand response (DR) is a crucial component of power systems that can offer operating
reserves by utilizing flexible loads on the demand side. With the development of …

This paper presents a unified framework for distributed filtering and control of state-space
processes. To this end, a distributed Kalman filtering algorithm is developed via …

In recent years, a compelling need has arisen to understand the effects of distributed
information structures on estimation and filtering. In this study, a bibliographical review on …

Consensus-based algorithms for distributed Kalman filtering of the state of a dynamical
target agent have attracted considerable research and attention during the past decade. In …

In this paper a new decentralized computational structure is developed for Optimal state
estimation in large scale linear interconnected dynamical systems. The new filter uses a …

One of the fundamental problems in sensor networks is to estimate and track the state of
targets (or dynamic processes) of interest that evolve in the sensing field. Kalman filtering …

Cyber-physical systems (CPSs) empower the integration of physical processes and cyber
infrastructure with the aid of ubiquitous computation resources and communication …

Information and communication technology tremendously facilitates the operation efficiency
and economy of modern power systems in recent years. However, risks such as bandwidth …