Michael O'Connell — accepted AI-conference papers

2024

Learning-Based Minimally-Sensed Fault-Tolerant Adaptive Flight Control

Michael O'Connell, Joshua Cho, Matthew Anderson, Soon-Jo Chung

RA-L 2024

Many multirotor aircraft use redundant configurations to maintain control in the event of an actuator failure. Due to the redundancy of the system, fault isolation is inherently difficult and further compounded by complex interacting aerodynamics of the propellers, wings, and body. This paper presen

Cited by 9 Source ↗Scholar ↗

2021

Meta-Adaptive Nonlinear Control: Theory and Algorithms

Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue

NeurIPS 2021poster

We present an online multi-task learning approach for adaptive nonlinear control, which we call Online Meta-Adaptive Control (OMAC). The goal is to control a nonlinear system subject to adversarial disturbance and unknown \emph{environment-dependent} nonlinear dynamics, under the assumption that the…

Cited by 50 Source ↗PDF ↗code ↗Scholar ↗