Abstract
This study proposes the design of learning-based discrete-time Luenberger observers for the global reconstruction of discrete-time multi-tone sinusoidal signals with unknown frequencies while avoiding the use of adaptive techniques. The unknown parameters are estimated directly using an explicit nonlinear mapping which achieves exponential convergence to the true unknown parameters. The proposed observer is applied in the design of a feedforward controller that solves the output regulation problem.
| Original language | English |
|---|---|
| Title of host publication | 2025 American Control Conference, ACC 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2503-2508 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331569372 |
| ISBN (Print) | 9798350367614 |
| DOIs | |
| Publication status | Published - 2025 |
| Externally published | Yes |
| Event | 2025 American Control Conference, ACC 2025 - Denver, United States Duration: 8 Jul 2025 → 10 Jul 2025 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| ISSN (Print) | 0743-1619 |
Conference
| Conference | 2025 American Control Conference, ACC 2025 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 8/07/25 → 10/07/25 |
Bibliographical note
Publisher Copyright:© 2025 AACC.
Funding
This research was supported by the U.S. Food and Drug Administration under the FDA BAA-22-00123 program, Award Number 75F40122C00200.
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