BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:ADMM for Exploiting Structure in MPC Problems - Felix Rey\, ETH Zu
 rich
DTSTART:20180222T140000Z
DTEND:20180222T150000Z
UID:TALK100525@talks.cam.ac.uk
CONTACT:Alberto Padoan
DESCRIPTION:Model predictive control (MPC) handles a control task by the r
 ecurrent solution of an optimization problem. The resulting computational 
 burden calls for efficient optimization\, particularly under cost and perf
 ormance pressure. As several publications testify\, efficiency is improved
  when the congruence or fit between control hardware\, optimization algori
 thm\, and problem structure is high\, meaning that these elements are well
 -adjusted to each other. We consider embedded platforms such as FPGAs\, an
 d we use the alternating direction method of multipliers (ADMM) as the opt
 imization algorithm. We tailor this setup to MPC-type problems\, letting A
 DMM exploit the problem structure while taking the best of the embedded pl
 atform. Most notably\, we exploit interacting components in the controlled
  system by decomposing it into virtual subsystems. The resulting structure
 -exploiting algorithm shows the following characteristics: (i) it is highl
 y parallelizable\, suiting the availability of parallel threads on embedde
 d hardware\; (ii) it scales favorably with the problem size\; and (iii) ev
 en for a single-thread implementation\, given that the controlled system i
 s sufficiently structured\, it improves overall performance.\n
LOCATION:Cambridge University Engineering Department\, Lecture Room number
  LR12
END:VEVENT
END:VCALENDAR