Global vs local: A comparison of two approaches to perform diagnosis in networks of mechatronic agents

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Natural systems often exhibit, at a macro level, a tendency to order that emerges from simple and local interactions between the system components. This idea that the whole can denote a consistent behavior that is more than the sum of individual components has inspired the design and development of many artificial systems. Recently, with the pervasiveness of IT in the automation domain the application of such principles became interesting as a mean to developed seamlessly pluggable, robust and fault-tolerant mechatronic systems. These concepts, however, have been mainly applied from a control perspective. This paper argues the regulatory significance of diagnosis in such complex systems and discusses two strategies (fully centralized with global information and fully decentralized with local information) to perform a diagnostic analysis that explores the network dimension of future mechatronic systems.

Original languageEnglish
Title of host publicationProceedings - 2010 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2010
Pages84-93
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2010 - Budapest, Hungary
Duration: 27 Sept 20101 Oct 2010

Conference

Conference2010 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2010
Country/TerritoryHungary
CityBudapest
Period27/09/101/10/10

Keywords

  • Automation
  • Complex systems
  • Distributed diagnosis
  • Evolvable production systems

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