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SUMMARY:Control of Lumped-Distributed Control Systems - Richard Vinter\, I
 mperial College
DTSTART:20260219T140000Z
DTEND:20260219T150000Z
UID:TALK244723@talks.cam.ac.uk
CONTACT:Jan Maciejowski
DESCRIPTION:Lumped-distributed control systems are collections of interact
 ing sub-systems\, some of which have finite dimensional vector state space
 s (comprising ‘lumped’ components) and some of which have infinite dim
 ensional vector state spaces (comprising ‘distributed’ components). Lu
 mped-distributed control systems are encountered\, for example\, in models
  of thermal or distributed mechanical devices under boundary control\, whe
 n we take account of control actuator dynamics or certain kinds of dynamic
  loading effects. \nThis talk will focus on an important class of (possibl
 y non-linear) lumped-distributed control systems\, in which the control ac
 tion directly affects only the lumped sub-systems and the output is a func
 tion of the lumped state variables alone. We give examples of such systems
 \, including a temperature-controlled test bed for measuring semiconductor
  material properties under changing temperature conditions and robot arms 
 with flexible links.\nA key observation is that there exists an exact repr
 esentation of the mapping from control inputs to outputs\, in terms of a f
 inite dimensional control system with memory. (We call it the reduced syst
 em representation). The reduced system representation can be seen as a tim
 e-domain analogue of frequency response descriptions involving the transfe
 r function from input to output. It is however much broader because\, in c
 ontrast to frequency response descriptions\, the reduced system representa
 tion allows non-linear dynamics\, hard constraints on controls and outputs
  and non-zero initial data.\nWe shall report on recent case studies that i
 llustrate the computational advantages of the reduced system representatio
 n. We show that\, for related output tracking improved tracking and reduct
 ion in computation time\, as compared with traditional methods\, based on 
 the approximation of infinite dimensional state spaces by high dimensional
  linear subspaces.
LOCATION:JDB Seminar Room\, Department of Engineering.
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