University of Twente Student Theses
Robust data-driven state-feedback synthesis from data corrupted by perturbations with bounded norms and rates-of-variation
Boer, Rens de (2023) Robust data-driven state-feedback synthesis from data corrupted by perturbations with bounded norms and rates-of-variation.
This is the latest version of this item.
|
PDF
3MB |
| Abstract: | Data-driven H∞-optimal controller synthesis is considered for unknown discrete-time linear time-invariant systems. Perturbations in the data, such as those coming from external disturbances and measurement noise, are assumed to be bounded in norm and rate-of-variation. A linear matrix inequality (LMI) based framework is presented in which these realistic bounds can be included in the synthesis. This reduces the set of systems consistent with the data and thus offers a reduction in conservatism, at the cost of increased computational complexity. The method is evaluated through simulations on a double pendulum system. |
| Item Type: | Essay (Master) |
| Faculty: | ET: Engineering Technology |
| Programme: | Mechanical Engineering MSc (60439) |
| Link to this item: | https://purl.utwente.nl/essays/97970 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page