6 citations · 9 across the 7 of their papers we have counts for
7 papers
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…
A Low Rank Approach to Minimize Sensor-to-Actuator Communication in Finite Horizon Output Feedback
Antoine Aspeel, Jakob Nylof, Jing Shuang Li +1
Many modern controllers are composed of different components that communicate in real-time over some network with limited resources. In this work, we are interested in designing a…
Koopman-inspired Implicit Backward Reachable Sets for Unknown Nonlinear Systems
Haldun Balim, Antoine Aspeel, Zexiang Liu +1
Koopman liftings have been successfully used to learn high dimensional linear approximations for autonomous systems for prediction purposes, or for control systems for leveraging l…
Quantifying the Value of Preview Information for Safety Control
Zexiang Liu, Necmiye Ozay
Safety-critical systems, such as autonomous vehicles, often incorporate perception modules that can anticipate upcoming disturbances to system dynamics, expecting that such preview…
Probabilistic Constraint Construction for Network-safe Load Coordination
Sunho Jang, Necmiye Ozay, Johanna L Mathieu
Distributed Energy Resources (DERs) can provide balancing services to the grid, but their power variations might cause voltage and current constraint violations in the distribution…
Finite Sample Identification of Bilinear Dynamical Systems
Yahya Sattar, Samet Oymak, Necmiye Ozay
Bilinear dynamical systems are ubiquitous in many different domains and they can also be used to approximate more general control-affine systems. This motivates the problem of lear…