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Feedback Scheduling of Model Predictive Controllers

Henriksson, Dan LU ; Cervin, Anton LU ; Åkesson, Johan LU and Årzén, Karl-Erik LU (2002) In Proceedings of the 8th IEEE Real-Time and Embedded Technology and Applications Symposium p.207-216
Abstract
The paper presents some preliminaryresults on dynamic scheduling of model predictive controllers (MPCs).In an MPC, the control signal is obtained by on-line optimization of acost function, and the MPC task may experience very large variationsin execution time from sample to sample. Unique to this application,the cost function offers an explicit, on-line quality-of-servicemeasure for the task. Based on this insight, a feedback schedulingstrategy for multiple MPCs is proposed, where the scheduler allocatesCPU time to the tasks according to the current values of the costfunctions. Since the MPC algorithm is iterative, the feedbackscheduler may also abort a task prematurely to avoid excessiveinput-output latency. A case study is presented,... (More)
The paper presents some preliminaryresults on dynamic scheduling of model predictive controllers (MPCs).In an MPC, the control signal is obtained by on-line optimization of acost function, and the MPC task may experience very large variationsin execution time from sample to sample. Unique to this application,the cost function offers an explicit, on-line quality-of-servicemeasure for the task. Based on this insight, a feedback schedulingstrategy for multiple MPCs is proposed, where the scheduler allocatesCPU time to the tasks according to the current values of the costfunctions. Since the MPC algorithm is iterative, the feedbackscheduler may also abort a task prematurely to avoid excessiveinput-output latency. A case study is presented, where the newapproach is compared to conventional fixed-priority andearliest-deadline-first scheduling. General problems related to thereal-time implementation of MPCs are also discussed. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Feedback Scheduling, Optimization, Model predictive control, Quality-of-service
in
Proceedings of the 8th IEEE Real-Time and Embedded Technology and Applications Symposium
pages
207 - 216
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000178662300020
  • scopus:84884336293
ISBN
0-7695-1739-0
DOI
10.1109/RTTAS.2002.1137395
language
English
LU publication?
yes
id
b727c3fc-668e-4a7c-b225-fb003a0615c2 (old id 537616)
date added to LUP
2007-09-19 15:59:33
date last changed
2017-03-12 04:24:32
@inproceedings{b727c3fc-668e-4a7c-b225-fb003a0615c2,
  abstract     = {The paper presents some preliminaryresults on dynamic scheduling of model predictive controllers (MPCs).In an MPC, the control signal is obtained by on-line optimization of acost function, and the MPC task may experience very large variationsin execution time from sample to sample. Unique to this application,the cost function offers an explicit, on-line quality-of-servicemeasure for the task. Based on this insight, a feedback schedulingstrategy for multiple MPCs is proposed, where the scheduler allocatesCPU time to the tasks according to the current values of the costfunctions. Since the MPC algorithm is iterative, the feedbackscheduler may also abort a task prematurely to avoid excessiveinput-output latency. A case study is presented, where the newapproach is compared to conventional fixed-priority andearliest-deadline-first scheduling. General problems related to thereal-time implementation of MPCs are also discussed.},
  author       = {Henriksson, Dan and Cervin, Anton and Åkesson, Johan and Årzén, Karl-Erik},
  booktitle    = {Proceedings of the 8th IEEE Real-Time and Embedded Technology and Applications Symposium},
  isbn         = {0-7695-1739-0},
  keyword      = {Feedback Scheduling,Optimization,Model predictive control,Quality-of-service},
  language     = {eng},
  pages        = {207--216},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Feedback Scheduling of Model Predictive Controllers},
  url          = {http://dx.doi.org/10.1109/RTTAS.2002.1137395},
  year         = {2002},
}