Cart (Loading....) | Create Account
Close category search window
 

Robust Parameter Estimation of Nonlinear Systems Using Sliding-Mode Differentiator Observer

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Iqbal, M. ; Center for Adv. Studies in Eng., Islamabad, Pakistan ; Bhatti, A.I. ; Ayubi, S.I. ; Khan, Q.

This paper presents the design, simulation, and experimental results of a new scheme for the robust parameter estimation of uncertain nonlinear dynamic systems. The technique is established on the estimation of robust time derivatives using a variable-structure differentiator observer. A second-order sliding motion is established along designed sliding manifolds to estimate the time derivatives of flat outputs and inputs, leading to better tracking performance of estimates during transients. The parameter convergence and accuracy analysis is rigorously explored systematically for the proposed class of estimators. The proposed method is validated using two case studies; first, the parameters of an uncertain nonlinear system with known, but uncertain nominal parametric values are estimated to demonstrate the convergence, accuracy, and robustness of the scheme; in the second application, the experimental parameter estimation of an onboard-diagnosis-II-compliant automotive vehicle engine is presented. The estimated parameters of the automotive engine are used to tune the theoretical mean value engine model having inaccuracies due to modeling errors and approximation assumptions. The resulting dynamics of the tuned engine model matches exactly with experimental engine data, verifying the accuracy of the estimates.

Published in:

Industrial Electronics, IEEE Transactions on  (Volume:58 ,  Issue: 2 )

Date of Publication:

Feb. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.