11 papers
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 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…
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 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…
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…
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…