Fiscal Year	2019
Division	Graduate School of Engineering & Applied Science
Department	Mechanical & Aerospace Engineering
Investigator(s)	Karpenko, Mark
Sponsor	Department of Defense Space (DoD)
Summary	The objective of this project is to utilize machine-learning/AI-based concepts for increasing the agility of CMG attitude control systems. We intend to design and implement an obstacle avoidance-based approach for finding full-envelope CMG momentum trajectories. This will be done by steering the momentum trajectory around gimbal lock “roadblocks”. As part of this project, we intend to perform hardware-in-the-loop simulations using our laboratory grade CMG array to demonstrate the new ideas.
Keywords	Obstacle Avoidance attitude control control moment gyroscope
Publications	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal