Divide and conquer identification using Gaussian process priors

Leith, D.J., Leithead, W.E., Solak, E. and Murray-Smith, R. (2002) Divide and conquer identification using Gaussian process priors. In: 41st IEEE Conference on Decision and Control, Las Vegas, Nevada, USA, 10-13 December 2002, pp. 624-629. ISBN 0780375165

Abstract

We investigate the reconstruction of nonlinear systems from locally identified linear models. It is well known that the equilibrium linearisations of a system do not uniquely specify the global dynamics. Information about the dynamics near to equilibrium provided by the equilibrium linearisations is therefore combined with other information about the dynamics away from equilibrium provided by suitable measured data. That is, a hybrid local/global modelling approach is considered. A non-parametric Gaussian process prior approach is proposed for combining in a consistent manner these two distinct types of data. This approach seems to provide a framework that is both elegant and powerful, and which is potentially in good accord with engineering practice.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Murray-Smith, Professor Roderick
• Authors: Leith, D.J., Leithead, W.E., Solak, E., and Murray-Smith, R.
• Subjects: T Technology > TJ Mechanical engineering and machinery
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• ISBN: 0780375165
• Copyright Holders: Copyright © 2002 Institute of Electrical and Electronics Engineers (IEEE)
• First Published: First published in Proceedings of the 41st IEEE Conference on Decision and Control
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher