3 citations · 3 across the 14 of their papers we have counts for
14 papers · 1 filter
Data-Driven Formal Methods for Complex Dynamical Systems: A Survey
Behrad Samari, Alessandro Abate, Antoine Girard +3
Data-driven approaches with formal guarantees have recently emerged as a powerful means for the verification and controller synthesis of complex dynamical systems. Interest in thes…
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…
Safety Controller Synthesis for Stochastic Polynomial Time-Delayed Systems
Omid Akbarzadeh, MohammadHossein Ashoori, Amy Nejati +1
This work develops a theoretical framework for safety controller synthesis in discrete-time stochastic nonlinear polynomial systems subject to time-invariant delays (dt-SNPS-td). W…
A Data-Driven Krasovskii-Based Approach for Safety Controller Design of Time-Delayed Uncertain Polynomial Systems
Omid Akbarzadeh, MohammadHossein Ashoori, Amy Nejati +1
We develop a data-driven framework for the synthesis of robust Krasovskii control barrier certificates (RK-CBC) and corresponding robust safety controllers (R-SC) for discrete-time…
From Formal Methods to Data-Driven Safety Certificates of Unknown Large-Scale Networks
Omid Akbarzadeh, Behrad Samari, Amy Nejati +1
In this work, we propose a data-driven scheme within a compositional framework with noisy data to design robust safety controllers in a fully decentralized fashion for large-scale…
Data-Efficient Control of Polynomial Systems via Physics-Guided Quadratic Constraints
MohammadHossein Ashoori, Ali Aminzadeh, Amy Nejati +1
This work addresses the critical challenge of guaranteeing safety for complex dynamical systems where precise mathematical models are uncertain and data measurements are corrupted…
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…
TRUST: Stability and Safety Controller Synthesis for Unknown Dynamical Models Using a Single Trajectory
Jamie Gardner, Ben Wooding, Amy Nejati +1
TRUST is an open-source software tool developed for data-driven controller synthesis of dynamical systems with unknown mathematical models, ensuring either stability or safety prop…
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…
Model Order Reduction from Data with Certification
Behrad Samari, Amy Nejati, Abolfazl Lavaei
Model order reduction (MOR) involves offering low-dimensional models that effectively approximate the behavior of complex high-order systems. Due to potential model complexities an…
A Physics-Informed Scenario Approach with Data Mitigation for Safety Verification of Nonlinear Systems
Ali Aminzadeh, MohammadHossein Ashoori, Amy Nejati +1
This paper develops a physics-informed scenario approach for safety verification of nonlinear systems using barrier certificates (BCs) to ensure that system trajectories remain wit…
Data-Driven Control of Large-Scale Networks with Formal Guarantees: A Small-Gain Free Approach
Behrad Samari, Amy Nejati, Abolfazl Lavaei
This paper offers a data-driven divide-and-conquer strategy to analyze large-scale interconnected networks, characterized by both unknown mathematical models and interconnection to…
From Data to Control: A Formal Compositional Framework for Large-Scale Interconnected Networks
Omid Akbarzadeh, Amy Nejati, Abolfazl Lavaei
We introduce a compositional data-driven methodology with noisy data for designing fully-decentralized safety controllers applicable to large-scale interconnected networks, encompa…