# Structured Output Feedback Control for Linear Quadratic Regulator Using Policy Gradient Method

arXiv: https://arxiv.org/abs/2203.00289 · HTML: https://mlsanity.com/paper/2203.00289/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2022.

## Built on by (most cited first, 3 of 3)

- [Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic Data](https://mlsanity.com/paper/2502.19977/) (2025)
- [Policy Gradient Method for LQG Control via Input-Output-History Representation: Convergence to O(ε)-Stationary Points](https://mlsanity.com/paper/2510.19141/) (2025)
- [Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Control](https://mlsanity.com/paper/2507.19895/) (2025)

## 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.