Robust subspace predictive control based on integral sliding mode for a pressurized water reactor
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
This work combines the subspace predictive control technique with the integral sliding mode control strategy to formulate a novel robust subspace predictive control scheme. The subspace predictive controller provides the nominal control whereas the integral sliding mode controller gives the discontinuous control action. The aim is to improve the capability of subspace predictive controller in handling uncertainties and external disturbances. The proposed control scheme is evaluated with a simulated pressurized water nuclear reactor. The effectiveness of the proposed technique is demonstrated for two different load-following operations in the presence of uncertainties.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 7th International Conference on Control, Decision and Information Technologies (CoDIT'2020) |
| Publisher | Institute of Electrical and Electronics Engineers |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-7281-5953-9, 978-1-7281-5952-2 |
| ISBN (Print) | 978-1-7281-5954-6 |
| DOIs | |
| Publication status | Published - 27 Nov 2020 |
| Event | 7th International Conference on Control, Decision and Information Technologies - Prague, Czech Republic Duration: 29 Jun 2020 → 2 Jul 2020 https://codit2020.com/index.php/ |
Publication series
| Name | Proceedings of the 7th International Conference on Control, Decision and Information Technologies (CoDIT) |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 2576-354 |
| ISSN (Electronic) | 2576-3555 |
Conference
| Conference | 7th International Conference on Control, Decision and Information Technologies |
|---|---|
| Abbreviated title | CoDIT 2020 |
| Country | Czech Republic |
| City | Prague |
| Period | 29/06/20 → 2/07/20 |
| Internet address |
Documents
- CODIT_RSPC
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Accepted author manuscript (Post-print), 481 KB, PDF document
Related information
ID: 20779622
