Modern Control System Learning
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Authors
Smeresky, Brendon
Rizzo, Alex
Subjects
control systems
feedforward
feedback
learning systems
feedforward
feedback
learning systems
Advisors
Date of Issue
2020
Date
Publisher
IntechOpen
Language
Abstract
This manuscript will explore and analyze the effects of different controllers in an overall spacecraft’s attitude determination and control system (ADCS). The experimental setup will include comparing an ideal nonlinear feedforward control- ler, a feedback controller, and a combined ideal nonlinear feedforward + feedback controller within a Simulink simulation. A custom proportional, derivative, integral controller was implemented in the feedback control, adding an additional term to account for the nonlinear coupled motion. Consistent proportional, derivative, and integral gains were used throughout the duration of the experiment. The simulated results will show that the ideal nonlinear feedforward controller lacked an error correction mechanism and took extra time to execute, the feedback controller faired only slightly better, but the combined ideal nonlinear feedforward controller with feedback correction yielded the highest accuracy with the lowest execution time. This highlights the potential effectiveness for a learning control system.
Type
Book Chapter
Description
From "Deterministic Artificial Intelligence" (2020) edited by Timothy Sands, https://doi.org/10.5772/intechopen.81309
Series/Report No
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NPS Report Number
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Funding
Format
11 p.
Citation
Smeresky, Brendon, and Alex Rizzo. "Modern Control System Learning." Deterministic Artificial Intelligence (2020): 153.
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.