Presents a data-driven value iteration algorithm for output-feedback LQR that recovers the optimal state-feedback gain via a non-minimal realization constructed from Kreisselmeier's adaptive filter.
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Data-Driven Linear Quadratic Control Using Output-Feedback via Non-Minimal Realization
Presents a data-driven value iteration algorithm for output-feedback LQR that recovers the optimal state-feedback gain via a non-minimal realization constructed from Kreisselmeier's adaptive filter.