12 citations · 28 across the 11 of their papers we have counts for
11 papers
Properties of Immersions for Systems with Multiple Limit Sets with Implications to Learning Koopman Embeddings
Zexiang Liu, Necmiye Ozay, Eduardo D. Sontag
Linear immersions (such as Koopman eigenfunctions) of a nonlinear system have wide applications in prediction and control. In this work, we study the properties of linear immersion…
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…
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…
Neural Architecture Search on Efficient Transformers and Beyond
Zexiang Liu, Dong Li, Kaiyue Lu +4
Recently, numerous efficient Transformers have been proposed to reduce the quadratic computational complexity of standard Transformers caused by the Softmax attention. However, mos…
On the Convergence of the Backward Reachable Sets of Robust Controlled Invariant Sets For Discrete-time Linear Systems
Zexiang Liu, Necmiye Ozay
This paper considers discrete-time linear systems with bounded additive disturbances, and studies the convergence properties of the backward reachable sets of robust controlled inv…
Automaton-based Implicit Controlled Invariant Set Computation for Discrete-Time Linear Systems
Zexiang Liu, Tzanis Anevlavis, Necmiye Ozay +1
In this paper, we derive closed-form expressions for implicit controlled invariant sets for discrete-time controllable linear systems with measurable disturbances. In particular, a…
Controlled invariant sets: implicit closed-form representations and applications
Tzanis Anevlavis, Zexiang Liu, Necmiye Ozay +1
We revisit the problem of computing (robust) controlled invariant sets for discrete-time linear systems. Departing from previous approaches, we consider implicit, rather than expli…
On the Value of Preview Information For Safety Control
Zexiang Liu, Necmiye Ozay
Incorporating predictions of external inputs, which can otherwise be treated as disturbances, has been widely studied in control and computer science communities. These predictions…
Scalable Computation of Controlled Invariant Sets for Discrete-Time Linear Systems with Input Delays
Zexiang Liu, Liren Yang, Necmiye Ozay
In this paper, we first propose a method that can efficiently compute the maximal robust controlled invariant set for discrete-time linear systems with pure delay in input. The key…
Safety Control with Preview Automaton
Zexiang Liu, Necmiye Ozay
This paper considers the problem of safety controller synthesis for systems equipped with sensor modalities that can provide preview information. We consider switched systems where…