Table of Contents
ISRN Signal Processing
Volume 2011 (2011), Article ID 725108, 18 pages
http://dx.doi.org/10.5402/2011/725108
Research Article

Iterative Smooth Variable Structure Filter for Parameter Estimation

Department of Mechanical Engineering, McMaster University, Hamilton, ON, Canada L8S 4L7

Received 28 February 2011; Accepted 20 March 2011

Academic Editors: I. Guler and E. Salerno

Copyright © 2011 Mohammad Al-Shabi and Saeid Habibi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The smooth variable structure filter (SVSF) is a recently proposed predictor-corrector filter for state and parameter estimation. The SVSF is based on the sliding mode control concept. It defines a hyperplane in terms of the state trajectory and then applies a discontinuous corrective action that forces the estimate to go back and forth across that hyperplane. The SVSF is robust and stable to modeling uncertainties making it suitable for fault detection application. The discontinuous action of the SVSF results in a chattering effect that can be used to correct modeling errors and uncertainties in conjunction with adaptive strategies. In this paper, the SVSF is complemented with a novel parameter estimation technique referred to as the iterative bi-section/shooting method (IBSS). This combined strategy is used for estimating model parameters and states for systems in which only the model structure is known. This combination improves the performance of the SVSF in terms of rate of convergence, robustness, and stability. The benefits of the proposed estimation method are demonstrated by its application to an electrohydrostatic actuator.