Online ResNet-Based Adaptive Control for Nonlinear Target Tracking
Fuente:
arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913866426875904 |
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| author | Nino, Cristian F. Patil, Omkar Sudhir Insinger, Jordan C. Eisman, Marla R. Dixon, Warren E. |
| author_facet | Nino, Cristian F. Patil, Omkar Sudhir Insinger, Jordan C. Eisman, Marla R. Dixon, Warren E. |
| contents | A generalized ResNet architecture for adaptive control of nonlinear systems with black box uncertainties is developed. The approach overcomes limitations in existing methods by incorporating pre-activation shortcut connections and a zeroth layer block that accommodates different input-output dimensions. The developed Lyapunov-based adaptation law establishes exponential convergence to a neighborhood of the target state despite unknown dynamics and disturbances. Furthermore, the theoretical results are validated through a comparative experiment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_14372 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Online ResNet-Based Adaptive Control for Nonlinear Target Tracking Nino, Cristian F. Patil, Omkar Sudhir Insinger, Jordan C. Eisman, Marla R. Dixon, Warren E. Systems and Control A generalized ResNet architecture for adaptive control of nonlinear systems with black box uncertainties is developed. The approach overcomes limitations in existing methods by incorporating pre-activation shortcut connections and a zeroth layer block that accommodates different input-output dimensions. The developed Lyapunov-based adaptation law establishes exponential convergence to a neighborhood of the target state despite unknown dynamics and disturbances. Furthermore, the theoretical results are validated through a comparative experiment. |
| title | Online ResNet-Based Adaptive Control for Nonlinear Target Tracking |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2503.14372 |