A comparison of software-based approaches to identifying FOPDT and SOPDT model parameters from process step response data
- Submitting institution
-
University of Sunderland
- Unit of assessment
- 12 - Engineering
- Output identifier
- 850
- Type
- D - Journal article
- DOI
-
10.1016/j.apm.2015.05.007
- Title of journal
- Applied Mathematical Modelling
- Article number
- -
- First page
- 100
- Volume
- 1
- Issue
- 1
- ISSN
- 0307-904X
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2016
- URL
-
http://sure.sunderland.ac.uk/id/eprint/5581/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- System identification is an experimental approach to deriving process models. Here, three methods are compared in the context of controller design for regulating processes. Since no model will contain the true system structure, the aim is to identify those providing an acceptable approximation in the context of the specific application. This paper compares for the first time modern software approaches that exploit step response data used to determine first or second order plus dead time transfer functions. They include an integral equation method, a powerful optimization algorithm, and software developed by the authors that uses a particle swarm optimisation approach.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -