Solving the linear quadratic regulator problem in the policy space: The Policy Algebraic Riccati Equation

The linear quadratic regulator problem is solved here within the policy space alone. To this end, a quadratic algebraic equation is envisioned to comprise only the entries of the optimal feedback matrix as unknown variables. As a consequence, the resulting equation contains, in general, much fewer quadratic equations than the corresponding Algebraic Riccati Equation and it permits the characterization of all the symmetric solutions of the latter. Furthermore, it is shown that the derived policy equation is amenable for an iterative solution via Newton’s method, which yields updated values identical to those obtained via the celebrated Kleinman’s algorithm.

Publication Details

Journal
Automatica
Published
2025-12-18
DOI
https://doi.org/10.1016/j.automatica.2025.112738
Primary Topic
Adaptive Dynamic Programming Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solving the linear quadratic regulator problem in the policy space: The Policy Algebraic Riccati Equation

Automatica
Adaptive Dynamic Programming Control
article

Solving the linear quadratic regulator problem in the policy space: The Policy Algebraic Riccati Equation

article en

Abstract

The linear quadratic regulator problem is solved here within the policy space alone. To this end, a quadratic algebraic equation is envisioned to comprise only the entries of the optimal feedback matrix as unknown variables. As a consequence, the resulting equation contains, in general, much fewer quadratic equations than the corresponding Algebraic Riccati Equation and it permits the characterization of all the symmetric solutions of the latter. Furthermore, it is shown that the derived policy equation is amenable for an iterative solution via Newton’s method, which yields updated values identical to those obtained via the celebrated Kleinman’s algorithm.

AutomaticaVol. 185
Peace, Justice and strong institutions
Openalex Percentile: Top 29%
Adaptive Dynamic Programming Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Solving the linear quadratic regulator problem in the policy space: The Policy Algebraic Riccati Equation · Automatica (2025) | TGRS Research Map | TGRS