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Distributed estimation techniques for cyber-physical systems: A systematic review

Authors

IERARDI, CARMELINA, ORIHUELA ESPINA, DIEGO LUIS, JURADO FLORES, ISABEL

External publication

No

Means

Sensors (Basel)

Scope

Review

Nature

Científica

JCR Quartile

SJR Quartile

JCR Impact

3.275

SJR Impact

0.653

Publication date

30/10/2019

ISI

000498834000117

Scopus Id

2-s2.0-85074324902

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 Physical System