Sinusoidal Trajectory Generation Methods for Spacecraft Feedforward Control
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Authors
Baker, Kyle A.
Subjects
sine wave approximation
sinusoidal trajectory generation
feedforward control
Taylor Series approximation
spacecraft torque generation
space vehicle rotational mechanics
SIMULINK
sinusoidal trajectory generation
feedforward control
Taylor Series approximation
spacecraft torque generation
space vehicle rotational mechanics
SIMULINK
Advisors
Date of Issue
2020
Date
2020
Publisher
InTech Open
Language
en_US
Abstract
The following is a brief walkthrough of material related to the modeling of spacecraft dynamics with feedforward control as the self-awareness declaration for deterministic artificial intelligence. Specifically, the focus will be on the analysis of various sinusoidal trajectory methods. The methods utilized are the basic MATLAB sine generation function, a Taylor series implementation, and two alter- nate algorithms for higher speed, lower precision and lower speed, higher precision implementations. The chapter features a brief summary of previous work investi- gating the impact of step size on Euler and Body angles. This is followed by a high level overview of Euler angle theory, quaternions, direction cosine matrices, kine- matics, and dynamics to form a mathematical basis for the core material. With the numerical basis for the modeling efforts outlined, the results of running a SIMULINK model of spacecraft dynamics with feedforward control will be briefly analyzed and explored. The analysis will cover the impacts of varying step size with various sinusoidal trajectory generation methodologies.
Type
Book Chapter
Description
From "Deterministic Artificial Intelligence" (2020) edited by Timothy Sands, https://doi.org/10.5772/intechopen.81309
Series/Report No
Department
Mechanical and Aerospace Engineering (MAE)
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
12 p.
Citation
Baker, Kyle A. "Sinusoidal Trajectory Generation Methods for Spacecraft Feedforward Control." Deterministic Artificial Intelligence (2020): 141.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.