Output feedback concurrent learning model reference adaptive control
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Quindlen15_GNC.pdf
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1.28 MB
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Author(s)
Quindlen, John Francis
How, Jonathan P
Date Issued
January 2015
Journal
AIAA Guidance, Navigation, and Control Conference
Publisher
American Institute of Aeronautics and Astronautics (AIAA)
Citation
John F. Quindlen et al. "Output Feedback Concurrent Learning Model Reference Adaptive Control", AIAA Guidance, Navigation, and Control Conference, 2015 January 5-9, Kissimmee, Florida, USA, American Institute of Aeronautics and Astronautics, 2015 © 2015 American Institute of Aeronautics and Astronautics
Version
Author's final manuscript
Abstract
Concurrent learning model reference adaptive control has recently been shown to guarantee simultaneous state tracking and parameter estimation error convergence to zero without requiring the restrictive persistency of excitation condition of other adaptive methods. This simultaneous convergence drastically improves the transient performance of the adaptive system since the true model is learned, but prior results were limited to systems with full state feedback. This paper presents an output feedback form of the concurrent learning controller for a novel extension to partial state feedback systems. The approach modifies a baseline LQG/LTR adaptive law with a recorded data stack of output and state estimate vectors. This maintains the guaranteed stability and boundedness of the baseline adaptive method, while improving output tracking error response. Simulations of exible aircraft dynamics demonstrate the improvement of the concurrent learning system over a baseline output feedback adaptive method.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.2514/6.2015-0607
