ModellingTopological Feasibility Guarantees for Differentiable Predictive ControlarXiv — Systems and Control (eess.SY) · yesterdayDigital twinOnline Data-Driven Reachability Analysis using Zonotopic Recursive Least SquaresarXiv — Systems and Control (eess.SY) · yesterdayDigital twinResults of Foresight Session on Cyber-Physical Systems Security PublishedspbIT · 22hDigital twinMachine Vision for Digital Twins, 3D Stereo Camera, AI Sensor GrowthVision Systems Design · yesterdayDigital twinAegis Secures $480K for Digital Twin ResearchPluang · yesterdayDigital twinFusionex AI Digital Twins Eliminate Production BottlenecksMacau Business · yesterdayDigital twinDigital Twin of Jinjiang River: Minute-Level Flood Response with 8000G Datasohu.com · yesterdayDigital twinSiemens to Apply Digital Twins in U.S. Army ManufacturingMobility Engineering Technology · yesterdayDigital twinStreaming Sparse Cholesky for Derivative-Informed Gaussian Process Surrogates in Digital TwinsarXiv — Computational Engineering, Finance, and Science (cs.CE) · yesterdayDigital twinA Pragmatic Guide to Building Conservative Discrete Abstractions of Cyber-Physical SystemsarXiv — Systems and Control (eess.SY) · yesterdayDigital twinMultisource Human-in-the-Loop Digital Twin Testbed for Connected and Autonomous Vehicles in Mixed Traffic FlowarXiv — Systems and Control (eess.SY) · yesterdayDigital twinDigital Twin Predicts Infrared Reflective Coating Can Cool by Several Degrees维度网 · yesterday
Streaming Sparse Cholesky for Derivative-Informed Gaussian Process Surrogates in Digital Twins
US & West ·
The paper presents an end-to-end digital twin solution for predicting the state of an aircraft structure. The method extends Gaussian processes to include derivative data for improved accuracy and uses a streaming sparse Cholesky factorization for efficient updating with in-service data. This enables real-time high-fidelity forecasting.
Why it matters
Demonstrates a practical approach to updating surrogate models with in-service data, which is critical for accurate forecasting of physical asset states in digital twins.
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.
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.
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.
