Abstract
This paper defines geometric criteria which are then used to establish sufficient conditions for persistency of excitation with vector functions constructed from single hidden-layer neural networks with step or ReLU activation functions. We show that these conditions hold when employing reference system tracking, as is commonly done in adaptive control. We demonstrate the results numerically on a system with linearly parameterized activations of this type and show that the parameter estimates converge to the true values with the sufficient conditions met.
| Original language | English (US) |
|---|---|
| Title of host publication | 2022 IEEE 61st Conference on Decision and Control, CDC 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2025-2030 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665467612 |
| DOIs | |
| State | Published - 2022 |
| Event | 61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico Duration: Dec 6 2022 → Dec 9 2022 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| Volume | 2022-December |
| ISSN (Print) | 0743-1546 |
| ISSN (Electronic) | 2576-2370 |
Conference
| Conference | 61st IEEE Conference on Decision and Control, CDC 2022 |
|---|---|
| Country/Territory | Mexico |
| City | Cancun |
| Period | 12/6/22 → 12/9/22 |
Bibliographical note
Funding Information:This work was supported in part by NSF CMMI-2122856 T. Lekang and A. Lamperski are with the department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA lekang@umn.edu, alampers@umn.edu
Publisher Copyright:
© 2022 IEEE.