This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state is ...

Nov 18, 2019 · Data-driven Linear Quadratic Regulation via Semidefinite Programming. This paper studies the finite-horizon linear quadratic regulation problem ...

We formulate the LQR problem as a (one-shot) semidefinite program in which the model of the system is replaced by a finite number of data collected from the ...

Abstract: This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state ...

Feb 27, 2021 · This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the ...

Abstract—We study the data-driven finite-horizon linear quadratic regularization (LQR) problem reformulated as a semidefinite program (SDP).

5 days ago · Abstract—In this paper, we study the noise sensitiv- ity of the semidefinite program (SDP) proposed for direct data-driven infinite-horizon ...

This letter presents a data-driven solution to the discrete-time infinite horizon linear quadratic regulator (LQR) problem. The state feedback gain is ...

Abstract. We present a data-driven method for solving the linear quadratic regulator problem for systems with multiplicative disturbances, the distribution ...

Jan 25, 2023 · This work presents a rather effective alternative optimization approach based on gradient projection. The utilized gradient is obtained through a data-driven ...