Full Content is available to subscribers

Subscribe/Learn More  >

An Intelligent Nonlinear System Identification Method With Robust State Estimation

[+] Author Affiliations
Jason R. Kolodziej

Rochester Institute of Technology, Rochester, NY

Paper No. DSCC2011-5970, pp. 361-367; 7 pages
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 1
  • Arlington, Virginia, USA, October 31–November 2, 2011
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5475-4
  • Copyright © 2011 by ASME


An approach is presented for nonlinear system identification by combining a proven state estimation technique, Minimum Model Error (MME) estimation, with a feed-forward neural network. The MME/NN hybrid algorithm first determines from measurement data a smooth state estimate of the system as well as identifying a correction to the assumed system model. Next, the state estimates are then used as training data for the neural network’s representation of the unmodeled system dynamics. The performance is then shown to be an improvement over a stand alone black-box neural network.

Copyright © 2011 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In