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Distributed Estimation Techniques for Cyber-Physical Systems: A Systematic Review.

Carmelina Ierardi1, Luis Orihuela2, Isabel Jurado3

  • 1Department of Engineering, Universidad Loyola Andalucía, 41704 Seville, Spain. Carmelina.ierardi@gmail.com.

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|November 2, 2019
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Summary
This summary is machine-generated.

This systematic review analyzes distributed estimation for cyber-physical systems (CPS). It compares various techniques, highlighting their application, design, data needs, and experimental validation, especially for biological systems.

Keywords:
cyber-physical systemsdistributed estimationsystematic review

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Area of Science:

  • Automation and Control
  • Cyber-Physical Systems (CPS)
  • Distributed Estimation

Background:

  • Systematic reviews (SRs) offer a rigorous approach to surveying research, though less common in control engineering.
  • Existing reviews often lack a standardized methodology adaptable to automation and control.

Purpose of the Study:

  • To conduct a systematic review of distributed estimation techniques for cyber-physical systems (CPS).
  • To adapt and apply SR guidelines from biosciences and computer sciences to the control field.
  • To provide a comprehensive comparison of existing distributed estimation methods in CPS literature.

Main Methods:

  • Systematic literature search and screening based on adapted SR guidelines.
  • Categorization of identified techniques by estimator type (e.g., Kalman filter, Bayesian filter).
  • Analysis of application domains within CPS, estimator design (decentralized vs. centralized), data requirements, and validation methods (simulations/experiments).

Main Results:

  • Identified and compared diverse distributed estimation techniques for CPS.
  • Detailed the characteristics of each technique, including specific applications and design choices.
  • Highlighted studies involving human, animal, or biological systems, noting specific estimation challenges and solutions.

Conclusions:

  • Systematic reviews provide valuable, objective insights into distributed estimation for CPS.
  • A clear comparison of techniques aids in selecting appropriate methods for specific CPS applications.
  • Further research is needed, particularly in applying these techniques to complex biological systems within CPS.