Data-Driven Identification of Networks of Dynamic Systems

by Michel Verhaegen, Chengpu Yu, and Baptiste Sinquin

0 ratings • 0 reviews • 0 shelved
Book cover for Data-Driven Identification of Networks of Dynamic Systems

Bookhype may earn a small commission from qualifying purchases. Full disclosure.

This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.
  • ISBN13 9781316515709
  • Publish Date 12 May 2022 (first published 27 April 2022)
  • Publish Status Active
  • Publish Country GB
  • Imprint Cambridge University Press
  • Edition New edition
  • Format Hardcover
  • Pages 320
  • Language English