290 citations · 601 across the 6 of their papers we have counts for
6 papers
Hierarchical Meta-learning-based Adaptive Controller
Fengze Xie, Guanya Shi, Michael O'Connell +2
We study how to design learning-based adaptive controllers that enable fast and accurate online adaptation in changing environments. In these settings, learning is typically done d…
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
Michael O'Connell, Guanya Shi, Xichen Shi +4
Executing safe and precise flight maneuvers in dynamic high-speed winds is important for the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the rel…
Meta-Adaptive Nonlinear Control: Theory and Algorithms
Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell +2
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 subje…
Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
Michael O'Connell, Guanya Shi, Xichen Shi +1
Realtime model learning proves challenging for complex dynamical systems, such as drones flying in variable wind conditions. Machine learning technique such as deep neural networks…
Numerical Predictive Control for Delay Compensation
Xichen Shi, Michael O'Connell, Soon-Jo Chung
We present a delay-compensating control method that transforms exponentially stabilizing controllers for an undelayed system into a sample-based predictive controller with numerica…
Neural Lander: Stable Drone Landing Control using Learned Dynamics
Guanya Shi, Xichen Shi, Michael O'Connell +5
Precise near-ground trajectory control is difficult for multi-rotor drones, due to the complex aerodynamic effects caused by interactions between multi-rotor airflow and the enviro…