The Many Facets of Information in Networked Estimation and Control

Posted: 8 May 2023

See all articles by Massimo Franceschetti

Massimo Franceschetti

University of California, San Diego (UCSD)

Mohammad Javad Khojasteh

Massachusetts Institute of Technology (MIT)

Moe Z. Win

Massachusetts Institute of Technology (MIT)

Date Written: May 2023

Abstract

Networked control systems, where feedback loops are closed over communication networks, arise in several domains, including smart energy grids, autonomous driving, unmanned aerial vehicles, and many industrial and robotic systems active in service, production, agriculture, and smart homes and cities. In these settings, the two main layers of the system, control and communication, strongly affect each other's performance, and they also reveal the interaction between a cyber-system component, represented by information-based computing and communication technologies, and a physical-system component, represented by the environment that needs to be controlled. The information access and distribution constraints required to achieve reliable state estimation and stabilization in networked control systems have been intensively studied over the course of roughly two decades. This article reviews some of the cornerstone results in this area, draws a map for what we have learned over these years, and describes the new challenges that we will face in the future. Rather than simply listing different results, we present them in a coherent fashion using a uniform notation, and we also put them in context, highlighting both their theoreticalinsights and their practical significance. Particular attention is given to recent developments related to decentralized estimation in distributed sensing and communication systems and the information-theoretic value of event timing in the context of networked control.

Suggested Citation

Franceschetti, Massimo and Khojasteh, Mohammad Javad and Win, Moe Z., The Many Facets of Information in Networked Estimation and Control (May 2023). Annual Review of Control, Robotics, & Autonomous Systems, Vol. 6, pp. 233-259, 2023, Available at SSRN: https://ssrn.com/abstract=4437741 or http://dx.doi.org/10.1146/annurev-control-042820-010811

Massimo Franceschetti (Contact Author)

University of California, San Diego (UCSD) ( email )

9500 Gilman Drive
La Jolla, CA 92093
United States

Mohammad Javad Khojasteh

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Moe Z. Win

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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