BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Data-driven modeling and control via spectral submanifolds - Georg
 e Haller\, ETH Zurich
DTSTART:20260313T160000Z
DTEND:20260313T170000Z
UID:TALK243409@talks.cam.ac.uk
CONTACT:Duncan Hewitt
DESCRIPTION:I discuss a dynamical systems alternative to neural networks i
 n the data-driven reduced-order modeling of nonlinear phenomena. Specifica
 lly\, the recent concept of spectral submanifolds (SSMs) provides very low
 -dimensional attractors in virtually all dynamics problems of physical imp
 ortance. A data-driven identification of the reduced dynamics on these SSM
 s gives a mathematically justified way to construct accurate and predictiv
 e reduced-order models for solids\, fluids\,  and controls without the use
  of governing equations. I illustrate this on physical problems including 
 structural vibrations\, fluid-structure interactions\, shear flows\, plant
  dynamics\, and the model-predictive control of soft robots.
LOCATION:MR2
END:VEVENT
END:VCALENDAR