An UKF‐based nonlinear system identification method using interpolation models and backward integration

An UKF‐based nonlinear system identification method using interpolation models and backward... In this paper, a novel identification method for nonlinear systems is proposed. This method utilizes linear interpolation models to describe the nonlinear forces of the physical models, and the unscented Kalman filter (UKF) method is adopted for the task of nonlinear identification. With the help of a linear interpolation algorithm, the proposed method requires little prior knowledge of the form of the nonlinear stiffness. Therefore, this method takes advantage of both the independence of the linear interpolation points and the inherent mathematical properties of the UKF. The UKF method is also modified to better fit the needs of parameter identification. To further emphasize parameter identification, backward integration and observations of the previous states are used. Two numerical simulations of the nonlinear elastic stiffness and Bouc–Wen hysteresis are conducted to show the flexibility and efficiency of this method. In these 2 examples, the observation signals are generated by analytic models, and the identifications are conducted with a linear interpolation model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Structural Control and Health Monitoring Wiley

An UKF‐based nonlinear system identification method using interpolation models and backward integration

Loading next page...
 
/lp/wiley/an-ukf-based-nonlinear-system-identification-method-using-p0fxv04cbS
Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
1545-2255
eISSN
1545-2263
D.O.I.
10.1002/stc.2129
Publisher site
See Article on Publisher Site

Abstract

In this paper, a novel identification method for nonlinear systems is proposed. This method utilizes linear interpolation models to describe the nonlinear forces of the physical models, and the unscented Kalman filter (UKF) method is adopted for the task of nonlinear identification. With the help of a linear interpolation algorithm, the proposed method requires little prior knowledge of the form of the nonlinear stiffness. Therefore, this method takes advantage of both the independence of the linear interpolation points and the inherent mathematical properties of the UKF. The UKF method is also modified to better fit the needs of parameter identification. To further emphasize parameter identification, backward integration and observations of the previous states are used. Two numerical simulations of the nonlinear elastic stiffness and Bouc–Wen hysteresis are conducted to show the flexibility and efficiency of this method. In these 2 examples, the observation signals are generated by analytic models, and the identifications are conducted with a linear interpolation model.

Journal

Structural Control and Health MonitoringWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ;

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial