Motivation for Full-State Estimation [Control Bootcamp]

This video discusses the need for full-state estimation.  In particular, if we want to use full-state feedback (e.g., LQR), but only have limited measurements of the system, it is necessary to estimate the full state.

These lectures follow Chapter 8 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control"  by Brunton and Kutz

Amazon: https://www.amazon.com/Data-Driven-Sc...

Chapters available at: http://databookuw.com/databook.pdf
Book Website: http://databookuw.com
Brunton Website: eigensteve.com

This video was produced at the University of Washington

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• #control
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• #linear_algebra
• #eigenvalues
• #closed_loop
• #feedback
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• #estimation
• #kalman_filter
• #lqg
• #optimal_control