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Online Data-Driven Reachability Analysis using Zonotopic Recursive Least Squares
US & West ·
A data-driven reachability analysis method computes over-approximations of reachable sets directly from online state measurements, without requiring an accurate dynamic model. It estimates time-varying unknown models using an exponentially forgetting zonotopic recursive least squares method that handles bounded noise.
Why it matters
Data-driven reachability analysis is important for safety verification when accurate models are unavailable or unreliable, which is common in complex engineering systems.
The paper establishes deterministic feasibility guarantees for differentiable predictive control (DPC), a self-supervised approach for approximating explicit MPC policies. Through topological analysis of the induced reachable safe set, it shows DPC can guarantee feasibility without online safety filters.
The company Aktiv published the final document of a foresight session on the future of cyber-physical systems security in Russia. The document provides strategic recommendations and industry forecasts up to 2040.
The news covers the application of machine vision in digital twins, including 3D stereo cameras and the growth of AI sensors. It outlines technological trends in visual perception for simulation and monitoring.
