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SUMMARY:High-Performance Model Predictive Control for Medium-Voltage Drive
 s
DTSTART:20110520T111500
DTSTAMP:20260407T195945Z
UID:f41cc9cbc1b627cc8b9126016dfee5912e6375d51c22c1187ee40cf7
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Tobias Geyer\, University of Auckland\nModel predictive con
 trol (MPC) is rapidly emerging as a new methodology to achieve high-perfor
 mance closed-loop control of ac drives. MPC relies on an internal model\, 
 predictions\, an objective function\, an optimization stage and the so cal
 led receding horizon policy. By combining the inner current control loop w
 ith the modulation stage\, the gating signals can be directly generated by
  MPC in one computational stage. MPC computes switching patterns that simu
 ltaneously reduce the inverter’s switching losses and the current and to
 rque distortions. At the same time\, the drive’s controlled variables\, 
 which are either the currents or the torque and stator flux\, are kept aro
 und their references or within specified bounds. This talk provides an int
 roduction to MPC for ac drives and a review of the different emerging meth
 ods. It is shown how the related computational challenges\, which are due 
 to the combinatorial explosion of the number of admissible switching seque
 nces\, can be addressed. As a result\, at low switching frequencies\, the 
 resulting steady-state behaviour is similar to the one obtained with optim
 ized pulse patterns. During transients\, however\, very fast current and t
 orque response times are achieved\, similar to deadbeat control. Simulatio
 ns and selected experimental results will be presented to illustrate these
  performance characteristics\, using three- and five-level medium-voltage 
 drives with induction machines as illustrative examples.
LOCATION:ELA2 
STATUS:CONFIRMED
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