1 citations · 1 across the 6 of their papers we have counts for
6 papers
Computationally Efficient State and Model Estimation via Interval Observers for Partially Unknown Systems
Mohammad Khajenejad, Zeyuan Jin
This paper addresses the synthesis of interval observers for partially unknown nonlinear systems subject to bounded noise, aiming to simultaneously estimate system states and learn…
Resilient State Estimation for Nonlinear Discrete-Time Systems via Input and State Interval Observer Synthesis
Mohammad Khajenejad, Zeyuan Jin, Thach Ngoc Dinh +1
This paper addresses the problem of resilient state estimation and attack reconstruction for bounded-error nonlinear discrete-time systems with nonlinear observations/ constraints,…
Data-Driven Model Discrimination of Switched Nonlinear Systems with Temporal Logic Inference
Zeyuan Jin, Nasim Baharisangari, Zhe Xu +1
This paper addresses the problem of data-driven model discrimination for unknown switched systems with unknown linear temporal logic (LTL) specifications, representing tasks, that…
Resilient Interval Observer for Simultaneous Estimation of States, Modes and Attack Policies
Mohammad Khajenejad, Zeyuan Jin, Sze Zheng Yong
This paper considers the problem of designing interval observers for hidden mode switched nonlinear systems with bounded noise signals that are compromised by false data injection…
Interval Observers for Simultaneous State and Model Estimation of Partially Known Nonlinear Systems
Mohammad Khajenejad, Zeyuan Jin, Sze Zheng Yong
We study the problem of designing interval-valued observers that simultaneously estimate the system state and learn an unknown dynamic model for partially unknown nonlinear systems…
Data-Driven Model Invalidation for Unknown Lipschitz Continuous Systems via Abstraction
Zeyuan Jin, Mohammad Khajenejad, Sze Zheng Yong
In this paper, we consider the data-driven model invalidation problem for Lipschitz continuous systems, where instead of given mathematical models, only prior noisy sampled data of…