Structured Output Feedback Control for Linear Quadratic Regulator Using Policy Gradient Method
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Abstract (arXiv)
We consider the static output feedback control for Linear Quadratic Regulator problems with structured constraints under the assumption that system parameters are unknown. To solve the problem in the model free setting, we propose the policy gradient algorithm based on the gradient projection method and show its global convergence to varepsilon-stationary points. In addition, we introduce a variance reduction technique and show both theoretically and numerically that it significantly reduces the variance in the gradient estimation. We also show in the numerical experiments that the model free approach efficiently solves the problem.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Mar 2022.
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Citing papers per year: 2025: 3.
3 papers.
- 2025Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic Datacited by 2
- 2025Policy Gradient Method for LQG Control via Input-Output-History Representation: Convergence to O(ε)-Stationary Pointscited by 1
- 2025Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Controlcited by 0
- 2025Policy Gradient Method for LQG Control via Input-Output-History Representation: Convergence to O(ε)-Stationary Points22 Oct 2025
- 2025Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Control26 Jul 2025
- 2025Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic Data27 Feb 2025