4 papers
Benefits of Linear Dynamic State Feedback in Co-stabilization
Xiong Zeng, Necmiye Ozay, Mario Sznaier
Co-stabilization, i.e., designing a single controller that stabilizes multiple systems, is a fundamental problem in robust and data-driven control. While any stabilizable linear sy…
System Identification Under Bounded Noise: Optimal Rates Beyond Least Squares
Xiong Zeng, Jing Yu, Necmiye Ozay
System identification is a fundamental problem in control and learning, particularly in high-stakes applications where data efficiency is critical. Classical approaches, such as th…
Noise Sensitivity of the Semidefinite Programs for Direct Data-Driven LQR
Xiong Zeng, Laurent Bako, Necmiye Ozay
In this paper, we study the noise sensitivity of the semidefinite program (SDP) proposed for direct data-driven infinite-horizon linear quadratic regulator (LQR) problem for discre…
On the Hardness of Learning to Stabilize Linear Systems
Xiong Zeng, Zexiang Liu, Zhe Du +2
Inspired by the work of Tsiamis et al. \cite{tsiamis2022learning}, in this paper we study the statistical hardness of learning to stabilize linear time-invariant systems. Hardness…