Optimal Covariance Steering for Discrete-Time Linear Stochastic Systems

In this article, we study the optimal control problem for steering the state covariance of a discrete-time linear stochastic system over a finite time horizon. First, we establish the existence and uniqueness of the optimal control law for a quadratic cost function. Then, we show the separation of the optimal mean and the covariance steering problems. We also develop efficient computational methods to solve for the optimal control law, which is identified as the solution to a semidefinite program. The effectiveness of the proposed approach is demonstrated through numerical examples. In the process, we also obtain some novel theoretical results for a matrix Riccati difference equation, which may be of independent interest.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2024-10-02
DOI
https://doi.org/10.1109/tac.2024.3472788
Citations
18
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
5.58
Controls
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article

Optimal Covariance Steering for Discrete-Time Linear Stochastic Systems

Panagiotis Tsiotras, George Rapakoulias, Fengjiao Liu
18 citations
IEEE Transactions on Automatic Control
Advanced Control Systems Optimization
5.58
article

Optimal Covariance Steering for Discrete-Time Linear Stochastic Systems

Panagiotis Tsiotras, George Rapakoulias, Fengjiao Liu
article en
18 citations

Abstract

In this article, we study the optimal control problem for steering the state covariance of a discrete-time linear stochastic system over a finite time horizon. First, we establish the existence and uniqueness of the optimal control law for a quadratic cost function. Then, we show the separation of the optimal mean and the covariance steering problems. We also develop efficient computational methods to solve for the optimal control law, which is identified as the solution to a semidefinite program. The effectiveness of the proposed approach is demonstrated through numerical examples. In the process, we also obtain some novel theoretical results for a matrix Riccati difference equation, which may be of independent interest.

IEEE Transactions on Automatic ControlVol. 70(4)
Georgia Institute of Technology (US), Florida A&M University - Florida State University College of Engineering (US)
Openalex Percentile: Top 3%
Advanced Control Systems Optimization
5.58
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