In this paper, we provide a tutorial review of recent results in the design of distributed model
predictive control systems. Our goal is to not only conceptually review the results in this area …

Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked
systems enable the employment of multiple sensors. Distributed estimation provides a …

This work deals with the topic of information processing over graphs. The presentation is
largely self-contained and covers results that relate to the analysis and design of multi-agent …

This paper addresses distributed state estimation over a sensor network wherein each node–
equipped with processing, communication and sensing capabilities–repeatedly fuses local …

This note addresses Distributed State Estimation (DSE) over sensor networks. Two existing
consensus approaches for DSE, ie, consensus on information (CI) and consensus on …

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is
required to estimate the state of a linear dynamic system from in a collaborative manner. Our …

Gossip algorithms are attractive for in-network processing in sensor networks because they
do not require any specialized routing, there is no bottleneck or single point of failure, and …

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 …

If a system and its observation are both represented in state space with linear equations, the
system noise and the measurement noise are white, Gaussian, and mutually uncorrelated …

The paper addresses distributed multitarget tracking over a network of heterogeneous and
geographically dispersed nodes with sensing, communication and processing capabilities …