Adaptive Optimal Control for A Class of Nonlinear Systems: The Online Policy Iteration Approach
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 12 - Engineering
- Output identifier
- 173997696
- Type
- D - Journal article
- DOI
-
10.1109/TNNLS.2019.2905715
- Title of journal
- IEEE Transactions on NEural Networks and Learning Systems
- Article number
- -
- First page
- 549
- Volume
- 31
- Issue
- 2
- ISSN
- 2162-237X
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2019
- 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
-
4
- Research group(s)
-
F - EEE
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This result has been followed by several research groups, including those in Chung-Ang University, Seoul, and in Lakehead University, Canada. The result also contributed to Zhengtao Ding’s keynote speech in IRCE 2020 (http://www.irce.org/speakers.html). (http://www.cast.org.cn/art/2019/8/8/art_179_99996.html).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
