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Emerging robust and data‐driven control methods for uncertain learning systems.
- Source :
-
International Journal of Robust & Nonlinear Control . 5/10/2023, Vol. 33 Issue 7, p3962-3963. 2p. - Publication Year :
- 2023
-
Abstract
- Learning systems represent a particularly important class of practical data-driven systems that adapt to their environment based on the environment's response to the system's action. Despite the success of learning-based methods, finding suitable control frameworks for learning systems when there is uncertainty in the assumptions related to the system dynamics is still an open problem. They propose a novel constrained ILC design and further develop a decentralized implementation of the resulting ILC algorithm using the alternating direction method of multipliers, allowing the design to scale up to handle large-scale and varying system dynamics. [Extracted from the article]
Details
- Language :
- English
- ISSN :
- 10498923
- Volume :
- 33
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- International Journal of Robust & Nonlinear Control
- Publication Type :
- Academic Journal
- Accession number :
- 163020783
- Full Text :
- https://doi.org/10.1002/rnc.6621