A systematic design process for internal model average consensus estimators

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

In the dynamic average consensus problem, agents in a communication network use information from their immediate neighbors to track the average of the group's time-varying inputs. Estimators based on the internal model principle solve this decentralized averaging problem with zero steady-state tracking error while providing robustness to network topology changes, agent failures, and communication faults. We develop a systematic process for designing these estimators. By formulating estimator synthesis as a robust control problem, we decouple the design process from specific networks. This formulation allows us to use an existing robust pole placement method to design estimators that meet performance specifications for a set of networks.

Original languageEnglish (US)
Title of host publication2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5878-5883
Number of pages6
ISBN (Print)9781467357173
DOIs
StatePublished - Jan 1 2013
Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: Dec 10 2013Dec 13 2013

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other52nd IEEE Conference on Decision and Control, CDC 2013
CountryItaly
CityFlorence
Period12/10/1312/13/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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