NDLI: State Estimation in Spatially Distributed Cyber-Physical Systems: Bounds on Critical Measurement Drop Rates

Content Provider	IEEE Xplore Digital Library
Author	Deshmukh, S. Natarajan, B. Pahwa, A.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA (Deshmukh, S.; Natarajan, B.; Pahwa, A.)
Abstract	In this paper, we analyze Kalman filter (KF) based state estimation in spatially distributed cyber-physical systems. We consider a practical scenario, where sensors are arbitrarily deployed over an area to jointly sense a linear dynamical system. The sensors directly communicate their observations to a central state estimation unit over a lossy network resulting in: (1) random measurement losses; (2) partial observation updates in the Kalman filter. We analyze the stability of the state estimation process in this scenario, by establishing the conditions under which its steady state error covariance matrix is bounded. In contrast to previous pioneering work with intermittent observations [1], we consider a dispersed measurement scenario and establish bounds on critical measurement loss rates of individual sensor communication links. The analysis illustrates the trade-off between state estimation accuracy and the quality of underlying communication network. Our analysis is critical to quantify the stability of control operation for safe and efficient operation of a cyber-physical system.
Sponsorship	IEEE Comput. Soc.
Starting Page	157
Ending Page	164
File Size	611710
Page Count	8
File Format	PDF
ISBN	9781479902064
e-ISBN	9780769550411
DOI	10.1109/DCOSS.2013.23
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intermittent measurements Measurement uncertainty Cyber physical systems Kalman filter Loss measurement Stability analysis Stochastic stability Kalman filters Covariance matrices State estimation Convergence
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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