Identification of spatiotemporally invariant systems for control adaptation

Azeem Sarwar, Petros G. Voulgaris, Srinivasa M. Salapaka

Research output: Contribution to journalArticlepeer-review


We present a distributed projection algorithm for system identification of spatiotemporally invariant systems with the ultimate purpose of utilizing it in an indirect adaptive control scheme. Each subsystem communicates only with its immediate neighbors to share its current estimate along with a cumulative improvement index. On the basis of the cumulative improvement index, the best estimate available is picked in order to carry out the next iteration. For small estimation error, the scheme switches over to a "smart" averaging routine. The proposed algorithm guarantees to bring the local estimates arbitrarily close to one another, developing a "local consensus", which makes it amenable to control by the application of indirect distributed adaptive control schemes. It is also shown through simulations that the proposed algorithm has a clear advantage over the standard projection algorithm. Our proposed algorithm is also suitable for addressing the estimation problem in distributed networks that arise in a variety of applications, such as environment monitoring, target localization and potential sensor network problems.

Original languageEnglish (US)
Pages (from-to)2079-2092
Number of pages14
Issue number9
StatePublished - Sep 2012


  • Complex systems
  • Distributed parameter estimation
  • Identification
  • Interconnected systems
  • Local consensus
  • Spatially invariant
  • Spatiotemporal systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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