Application of Neuromorphic Attitude Control to High-Powered Rockets

In high-powered rocketry, a common phenomenon known as “weather cocking” causes the fuselage of a craft to tilt into oncoming wind at low airspeeds, causing inconsistent trajectory, low apogee, and undesirable lateral velocity during parachute deployment. In this study, the research team developed a Neuromorphic Control System (NCS) utilizing an aft nacelle with variable geometry. The software of this system uses physically informed architecture to actively predict and control disturbances due to wind, turbulence, and various transonic effects. This NCS employs spatial neuroplasticity to learn system physics, allowing sensory experiences to determine necessary control maneuvers. The validity of the system was determined by Computational Fluid Dynamics simulations, six degree-of-freedom trajectory control analysis, benchtop electronics testing, and scaled flight evaluation. By applying a neuromorphic model with the ability to grow and change, superior nonlinear control can be realized.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.2514/6.2025-97908
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
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article

Application of Neuromorphic Attitude Control to High-Powered Rockets

Kimberly J. Perez, Brian Davis, Susan Fountain, Daniel Bluedorn et al.
Adaptive Control of Nonlinear Systems
article

Application of Neuromorphic Attitude Control to High-Powered Rockets

Kimberly J. Perez, Brian Davis, Susan Fountain, Daniel Bluedorn, Kaiden Kiracofe
article en

Abstract

In high-powered rocketry, a common phenomenon known as “weather cocking” causes the fuselage of a craft to tilt into oncoming wind at low airspeeds, causing inconsistent trajectory, low apogee, and undesirable lateral velocity during parachute deployment. In this study, the research team developed a Neuromorphic Control System (NCS) utilizing an aft nacelle with variable geometry. The software of this system uses physically informed architecture to actively predict and control disturbances due to wind, turbulence, and various transonic effects. This NCS employs spatial neuroplasticity to learn system physics, allowing sensory experiences to determine necessary control maneuvers. The validity of the system was determined by Computational Fluid Dynamics simulations, six degree-of-freedom trajectory control analysis, benchtop electronics testing, and scaled flight evaluation. By applying a neuromorphic model with the ability to grow and change, superior nonlinear control can be realized.

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Adaptive Control of Nonlinear Systems
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