Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter
- Submitting institution
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Teesside University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 4048256
- Type
- D - Journal article
- DOI
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10.1109/TPEL.2017.2768618
- Title of journal
- IEEE Transactions on Power Electronics
- Article number
- -
- First page
- 8081
- Volume
- 33
- Issue
- 9
- ISSN
- 0885-8993
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
-
-
- 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
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3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- System identification is often not fully implemented for power electronic converters in real-time for low-cost, low-power applications (eg. point-of-load DC-DC converters) where it presents challenges in cost-sensitive applications and typically requires substantial hardware resources to be implemented. We propose a novel Partial-Update technique for the Kalman-Filter (KF) coefficients to reduce the computational cost for real-time identification of DC-DC model parameters. The computational load reduces by 50% of the traditional KF with comparable performance and accuracy. This research has resulted in on-going UK research collaboration between Teesside, Newcastle, and Aston Universities.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -