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UID:pretalx-amfc2026-PTKHHT@modelica.simtek.cc
DTSTART;TZID=CST:20260922T110500
DTEND;TZID=CST:20260922T113000
DESCRIPTION:Digital twin technology is central to Cyber-Physical Systems\, 
 yet purely data-driven approaches demand high computational resources and 
 expensive validation. Xu's Modular Modeling Method for Performance Paramet
 ers of Large-scale Hydraulic Systems ("Xu's Modeling Method")—a physical
  modeling technology from the 1980s implemented in the PERSIM software—s
 hares structural similarities with Modelica\, though their algorithms diff
 er. We extend Xu's method to mechanismbased digital twin modeling\, creati
 ng a grey-box approach that combines physical models with data. Using Mode
 lica\, we implement XAP (Xu's Algorithm Package)\, unifying simulation and
  digital twin modeling. A key contribution is an inverse operation framewo
 rk that recovers physical fault indicators from measured step-response dat
 a. Numerical validation shows that identifiable fault parameters—single\
 , dual\, and crosschamber multi-parameter combinations—are recovered wit
 h errors below 1%\, and the identifiability limit of joint estimation with
 in a chamber pair is characterized. The resulting grey-box method offers i
 nterpretable\, efficient digital twin modeling for motion control systems.
DTSTAMP:20261004T074206Z
LOCATION:Modelica Technology & AI (R1001)
SUMMARY:Theoretical Reconstruction of Xu's Digital Twin Modeling Method and
  Its Integration with the Modelica Environment - Lei Xiangli\, Quan Long\,
  Xu Yangzeng\, Wang Qixin\, Li Zepeng
URL:https://modelica.simtek.cc/amfc2026/talk/PTKHHT/
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