From the 1 of 36 linked papers with an AI index.
22 papers · 1 filter
Reachability Analysis With Probabilistic Zonotopes: Learning Realized Disturbances and Refining Aleatory Uncertainty
Amir Modares, Zhen Zhang, Themistoklis Charalambous +2
This paper develops a data-driven reachability framework for linear systems whose disturbances are modeled by probabilistic zonotopes (PZs), combining bounded deterministic and Gau…
Data-Driven Reachability Analysis Using Matrix Perturbation Theory
Peng Xie, Abdulla Fawzy, Zhen Zhang +1
We propose a matrix zonotope perturbation framework that leverages matrix perturbation theory to characterize how noise-induced distortions alter the dynamics within sets of models…
Orthogonal Transformations for Efficient Data-Driven Reachability Analysis
Peng Xie, Amr Alanwar
Data-driven reachability analysis using matrix zonotopes faces a fundamental challenge: the number of generators in the reachable set grows exponentially during propagation, while…
From Points to Sets: Set-Based Safety Verification in the Latent Space
Wenyuan Wu, Peng Xie, Zhen Zhang +3
We extend latent representation methods for safety control design to set-valued states. Recent work has shown that barrier functions designed in a learned latent space can transfer…
Bridging Data-Driven Reachability Analysis and Statistical Estimation via Constrained Matrix Convex Generators
Peng Xie, Zhen Zhang, Rolf Findeisen +1
Data-driven reachability analysis enables safety verification when first-principles models are unavailable. This requires constructing sets of system models consistent with measure…
Data-Driven Reachability Analysis with Optimal Input Design
Peng Xie, Davide M. Raimondo, Rolf Findeisen +1
This paper addresses the conservatism in data-driven reachability analysis for discrete-time linear systems subject to bounded process noise, where the system matrices are unknown…