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.
Adaptive optimal control for continuous-time linear systems based on policy iteration,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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The paper derives an algebraic condition for when data-knowledge pairs are jointly informative enough to uniquely solve Lyapunov equations.
citing papers explorer
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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.
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Informativity of Data-Knowledge Pairs for Lyapunov Equations
The paper derives an algebraic condition for when data-knowledge pairs are jointly informative enough to uniquely solve Lyapunov equations.