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Found 6 papers, 1 papers with code
Deep Learning Based Dynamics Identification and Linearization of Orbital Problems using Koopman Theory
We propose a data-driven framework for simultaneous system identification and global linearization of both the Two-Body Problem and Circular Restricted Three-Body Problem via deep learning-based Koopman Theory, i. e., a framework that can identify the underlying dynamics and globally linearize it into a linear time-invariant (LTI) system.
Computationally Efficient Data-Driven Discovery and Linear Representation of Nonlinear Systems For Control
This work focuses on developing a data-driven framework using Koopman operator theory for system identification and linearization of nonlinear systems for control.
Adaptive Modified RISE-based Quadrotor Trajectory Tracking with Actuator Uncertainty Compensation
This paper presents an adaptive robust nonlinear control method, which achieves reliable trajectory tracking control for a quadrotor unmanned aerial vehicle in the presence of gyroscopic effects, rotor dynamics, and external disturbances.
SpaceYOLO: A Human-Inspired Model for Real-time, On-board Spacecraft Feature Detection
Performance in autonomous spacecraft detection of SpaceYOLO is compared to ordinary YOLOv5 in hardware-in-the-loop experiments under different lighting and chaser maneuver conditions at the ORION Laboratory at Florida Tech.
Autonomous Satellite Docking via Adaptive Optimal Output Rregulation: A Reinforcement Learning Approach
The optimal control problem is presented using a data-driven reinforcement learning based method to regulate the relative position and velocity of the deputy to safely dock with the chief.
Autonomous Satellite Detection and Tracking using Optical Flow
In this paper, an autonomous method of satellite detection and tracking in images is implemented using optical flow.
