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SUMMARY:Predictive control of mechatronic systems - Abhishek Dutta\, PhD s
 tudent\, Ghent University
DTSTART:20130118T140000Z
DTEND:20130118T153000Z
UID:TALK42989@talks.cam.ac.uk
CONTACT:Dr Jason Z JIANG
DESCRIPTION:Control of mechatronic systems poses typical challenges i.e. n
 onlinear and fast dynamics with unknown optimal reference trajectories whi
 ch vary significantly in course of operation. In this context\, learning c
 ontrol for production machines has recently garnered attention from the re
 search community and special sessions in conferences and journals have bee
 n organized. We tackle such systems by a two-level learning control approa
 ch with (non)linear model-based control at lower level tracking references
  learned/adapted by a high level iterative leaning controller.\n\nMoreover
 \, many complex machines are non-collocated vibrating systems i.e. actuato
 rs and sensors do not act at the same point. We show that classical compen
 sators are incapable to control the induced oscillations and that model-ba
 sed controller synthesis and tuning for can deliver the required performan
 ce.\n\nThe above two methodologies are experimentally validated over a wet
 -clutch engagement and harvester height control. If time permits\, new ide
 as on extensions of closed-loop formulations of MPC for constrained system
 s will be touched on.
LOCATION:Cambridge University Engineering Department\, LR3B
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