A Note on State Parameterizations in Output Feedback Reinforcement Learning Control of Linear Systems

This note presents an analysis of the state parameterizations used in output feedback reinforcement learning (RL) control. Output feedback algorithms based on state parameterization involve additional conditions on the state parameterization beyond the standard conditions on the system matrices for...

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Veröffentlicht in:	IEEE transactions on automatic control 2023-10, Vol.68 (10), p.1-8
Hauptverfasser:	Rizvi, Syed Ali Asad, Lin, Zongli
Format:	Artikel
Sprache:	eng
Schlagworte:	adaptive dynamic programming Algorithms Control systems Convergence Linear systems Matrices (mathematics) Observability Observers optimal control Output feedback output feedback control Parameterization Q-learning Regulators Reinforcement learning State feedback state parameterization
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