Title Distributed estimation techniques for cyber-physical systems: A systematic review
Authors IERARDI, CARMELINA, ORIHUELA ESPINA, DIEGO LUIS, JURADO FLORES, ISABEL, ORIHUELA ESPINA, DIEGO LUIS, JURADO FLORES, ISABEL, IERARDI, CARMELINA
External publication No
Means Sensors
Scope Review
Nature Científica
JCR Quartile 1
SJR Quartile 2
JCR Impact 3.27500
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074324902&doi=10.3390%2fs19214720&partnerID=40&md5=027fcc5b389c74af4ac2346dbda6c51b
Publication date 01/01/2019
ISI 000498834000117
Scopus Id 2-s2.0-85074324902
DOI 10.3390/s19214720
Abstract This paper undertakes a systematic review (SR) on distributed estimation techniques applied to cyber-physical systems (CPS). Even though SRs are not the common way to survey a theme in the control community, they provide a rigorous, robust and objective formula that should not be always ignored. The presented SR incorporates and adapts the guidelines recommended in other fields (mainly biosciences and computer sciences) to the field of automation and control and presents a brief description of the different phases that constitute an SR. As a result, this review compares the different techniques found in the literature in terms of: The proposed estimator (Kalman filter, Luenberger observer, Bayesian filter, etc.), the particular application within CPS, the design of the estimators (decentralized vs centralized), the amount of data required for implementation or the inclusion of experiments/simulations in the studies. Particular attention is paid to those papers that present some results in applications that include humans, animals or biological systems. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Keywords Embedded systems; Kalman filters; Automation and controls; Bayesian filters; Control community; Cyber-physical systems (CPS); Distributed estimation; Luenberger observers; Systematic Review; Cyber Phy
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