By Topic

Modelling and identification for non-uniformly periodically sampled-data systems

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
$33 $33
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)
L. Xie ; Control Science and Engineering Research Center, Jiangnan University ; Y. J. Liu ; H. Z. Yang ; F. Ding

The authors state the non-uniformly periodically sampling pattern and derives the state-space models of non-uniformly sampled-data systems with coloured noises, and further obtains the corresponding transfer function models. Difficulties of identification are that there exist unknown inner variables and unmeasurable noise terms in the information vectors. By means of the auxiliary model method, an auxiliary model based multi-innovation generalised extended stochastic gradient (SG) algorithm is presented by expanding the scalar innovation to the innovation vector and introducing the innovation length. The proposed algorithm provides higher parameter estimation accuracy and faster convergence rate than the SG algorithm due to repeatedly using the system innovation.

Published in:

IET Control Theory & Applications  (Volume:4 ,  Issue: 5 )