By Topic

Subspace identification of multivariable LPV systems: a novel approach

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

2 Author(s)
van Wingerden, J. ; Delft Center for Syst. & Control, Delft Univ. of Technol., Delft ; Verhaegen, M.

In this paper we present a novel algorithm to identify LPV systems with affine parameter dependence. Ideas from closed-loop LTI subspace identification are used to formulate the input-output behavior of an LPV system. From this input-output behavior the LPV equivalent of the Markov parameters can be estimated. We show that with this estimate the product between the observability matrix and state sequence can be reconstructed and an SVD can be used to estimate the state sequence and consequently the system matrices. The curse of dimensionality in subspace LPV identification will appear and the kernel method is proposed as a partial remedy. The working of the algorithm is illustrated with two simulation examples.

Published in:

Computer-Aided Control Systems, 2008. CACSD 2008. IEEE International Conference on

Date of Conference:

3-5 Sept. 2008