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arXiv · 2503.14372

Online ResNet-Based Adaptive Control for Nonlinear Target Tracking

Cristian F. Nino·Omkar Sudhir Patil·Jordan C. Insinger·Marla R. Eisman·Warren E. Dixon
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Abstract

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.

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Cristian F. Nino, Omkar Sudhir Patil, Jordan C. Insinger, Marla R. Eisman, Warren E. Dixon. 2025-03-18. Online ResNet-Based Adaptive Control for Nonlinear Target Tracking. https://arxiv.org/abs/2503.14372

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