Guo, Y., Guo, L.Z., Billings, S.A. et al. (1 more author) (2016) Identification of continuous-time models for nonlinear dynamic systems from discrete data. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 47 (12). pp. 3044-3054. ISSN 0020-7721
Abstract
A new iOFR-MF (iterative orthogonal forward regression--modulating function) algorithm is proposed to identify continuous-time models from noisy data by combining the MF method and the iOFR algorithm. In the new method, a set of candidate terms, which describe different dynamic relationships among the system states or between the input and output, are first constructed. These terms are then modulated using the MF method to generate the data matrix. The iOFR algorithm is next applied to build the relationships between these modulated terms, which include detecting the model structure and estimating the associated parameters. The relationships between the original variables are finally recovered from the model of the modulated terms. Both nonlinear state-space models and a class of higher order nonlinear input–output models are considered. The new direct method is compared with the traditional finite difference method and results show that the new method performs much better than the finite difference method. The new method works well even when the measurements are severely corrupted by noise. The selection of appropriate MFs is also discussed.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2016 Taylor & Francis. This is an author produced version of a paper subsequently published in International Journal of Systems Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | modulating function method; nonlinear system identification; continuous-time model; iOFR algorithm; orthogonal forward regression |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 PROGRESS - 637302 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/I011056/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/H00453X/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Aug 2016 15:14 |
Last Modified: | 06 Aug 2017 13:30 |
Published Version: | http://dx.doi.org/10.1080/00207721.2015.1069906 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/00207721.2015.1069906 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103208 |