2 citations · 3 across the 9 of their papers we have counts for
10 papers · 1 filter
Data-Driven Stabilizing Controller Design for Linear Infinite Networks
Mahdieh Zaker, Andrii Mironchenko, Amy Nejati +1
We propose a direct data-driven method for controller synthesis of infinite networks composed of unknown linear time-invariant subsystems. Using a single set of noise-corrupted inp…
Data-Driven Global Stabilization of Unknown Infinite Networks
Mahdieh Zaker, Andrii Mironchenko, Amy Nejati +1
This paper develops a direct data-driven framework for infinite networks with unknown nonlinear polynomial subsystems, enabling the synthesis of controllers that ensure the entire…
Data-Driven Incremental GAS Certificate of Nonlinear Homogeneous Networks: A Scenario Approach with Noisy Data
Mahdieh Zaker, David Angeli, Abolfazl Lavaei
This work focuses on a compositional data-driven approach to verify incremental global asymptotic stability (delta-GAS) over interconnected homogeneous networks of degree one with…
Data-Driven Safety Certificates of Infinite Networks with Unknown Models and Interconnection Topologies
Mahdieh Zaker, Amy Nejati, Abolfazl Lavaei
Infinite networks are complex interconnected systems comprising a countably infinite number of subsystems, for which no fixed upper bound on the number of participating subsystems…
From Data to Global Asymptotic Stability of Unknown Large-Scale Networks with Provable Guarantees
Mahdieh Zaker, Amy Nejati, Abolfazl Lavaei
We offer a compositional data-driven scheme for synthesizing controllers that ensure global asymptotic stability (GAS) across large-scale interconnected networks, characterized by…
Abstraction-based Control of Unknown Continuous-Space Models with Just Two Trajectories
Behrad Samari, Mahdieh Zaker, Abolfazl Lavaei
Finite abstractions (a.k.a. symbolic models) offer an effective scheme for approximating the complex continuous-space systems with simpler models in the discrete-space domain. A cr…
Certified Learning of Incremental ISS Controllers for Unknown Nonlinear Polynomial Dynamics
Mahdieh Zaker, David Angeli, Abolfazl Lavaei
Incremental input-to-state stability (delta-ISS) offers a robust framework to ensure that small input variations result in proportionally minor deviations in the state of a nonline…
From a Single Trajectory to Safety Controller Synthesis of Discrete-Time Nonlinear Polynomial Systems
Behrad Samari, Omid Akbarzadeh, Mahdieh Zaker +1
This work is concerned with developing a data-driven approach for learning control barrier certificates (CBCs) and associated safety controllers for discrete-time nonlinear polynom…
Compositional Design of Safety Controllers for Large-Scale Stochastic Hybrid Systems
Mahdieh Zaker, Omid Akbarzadeh, Behrad Samari +1
In this work, we propose a compositional scheme based on small-gain reasoning to synthesize safety controllers for interconnected stochastic hybrid systems. In our proposed setting…
Rare Collision Risk Estimation of Autonomous Vehicles with Multi-Agent Situation Awareness
Mahdieh Zaker, Henk A. P. Blom, Sadegh Soudjani +1
This paper offers a formal framework for the rare collision risk estimation of autonomous vehicles (AVs) with multi-agent situation awareness, affected by different sources of nois…