Data-based predictive hybrid driven control for a class of imperfect networked systems
- Submitting institution
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The University of Warwick
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9304
- Type
- D - Journal article
- DOI
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10.1109/TII.2018.2799081
- Title of journal
- IEEE Transactions on Industrial Informatics
- Article number
- -
- First page
- 5187
- Volume
- 14
- Issue
- 11
- ISSN
- 1551-3203
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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-
- 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
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4
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, from collaborative research between University of Warwick (Innovate-UK fund, 104437), University of Ulsan and Korea Construction Equipment Technology Institute (KOCETI) (Korea fund, 20162020107450), was invited following presentation at IEEE-ICM2017. It proposed a novel, data-based predictive hybrid driven controller for robust tracking in networked control systems (<2% accuracy) disregarding network imperfections (random delays and/or package losses/disordering). This has allowed KOCETI to provide consulting services to OEMs making autonomous machines, contributing circa 10% to KOCETI revenue (£16m/2019) and their new projects (i.e. Korea Government funded: 20010590 £6.7m for excavators’ control valves; UM19401RD4 £2m for military tanks) (Jong Il Yoon, jiyoon@koceti.re.kr).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -