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Robust Penalty Adaptive Model Predictive Control (PAMPC) of constrained, underdamped, non-collocated systems

Abhishek Dutta, Clara-Mihaela Ionescu UGent, Mia Loccufier UGent and Robain De Keyser UGent (2016) JOURNAL OF VIBRATION AND CONTROL. 22(2). p.549-558
abstract
This paper investigates the control challenges posed by noncollocated mechatronic systems and motivates the need for a model-based control technique towards such systems. A novel way of online constraint handling by penalty adaptation (PAMPC) is proposed and shown to be of particular relevance towards robust control of underdamped, noncollocated systems by exploiting the structure of such systems. Further, a new tunneling approach is proposed for PAMPC to maintain feasibility under uncertainty. The PAMPC is shown to be optimal for control of a benchmark mass-spring-damper system, which poses all the mentioned challenges.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
Constrained, ALGORITHM, predictive control, optimal, robust
journal title
JOURNAL OF VIBRATION AND CONTROL
volume
22
issue
2
pages
549 - 558
publisher
Sage
Web of Science type
Article
Web of Science id
000368575200017
JCR category
ACOUSTICS
JCR impact factor
2.101 (2016)
JCR rank
9/31 (2016)
JCR quartile
2 (2016)
ISSN
1077-5463
DOI
10.1177/1077546314534282
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
7034204
handle
http://hdl.handle.net/1854/LU-7034204
date created
2016-01-12 10:26:32
date last changed
2016-12-19 15:48:17
@article{7034204,
  abstract     = {This paper investigates the control challenges posed by noncollocated mechatronic systems and motivates the need for a model-based control technique towards such systems. A novel way of online constraint handling by penalty adaptation (PAMPC) is proposed and shown to be of particular relevance towards robust control of underdamped, noncollocated systems by exploiting the structure of such systems. Further, a new tunneling approach is proposed for PAMPC to maintain feasibility under uncertainty. The PAMPC is shown to be optimal for control of a benchmark mass-spring-damper system, which poses all the mentioned challenges.},
  author       = {Dutta, Abhishek and Ionescu, Clara-Mihaela and Loccufier, Mia and De Keyser, Robain},
  issn         = {1077-5463},
  journal      = {JOURNAL OF VIBRATION AND CONTROL},
  keyword      = {Constrained,ALGORITHM,predictive control,optimal,robust},
  language     = {eng},
  number       = {2},
  pages        = {549--558},
  publisher    = {Sage},
  title        = {Robust Penalty Adaptive Model Predictive Control (PAMPC) of constrained, underdamped, non-collocated systems},
  url          = {http://dx.doi.org/10.1177/1077546314534282},
  volume       = {22},
  year         = {2016},
}

Chicago
Dutta, Abhishek, Clara-Mihaela Ionescu, Mia Loccufier, and Robain De Keyser. 2016. “Robust Penalty Adaptive Model Predictive Control (PAMPC) of Constrained, Underdamped, Non-collocated Systems.” Journal of Vibration and Control 22 (2): 549–558.
APA
Dutta, Abhishek, Ionescu, C.-M., Loccufier, M., & De Keyser, R. (2016). Robust Penalty Adaptive Model Predictive Control (PAMPC) of constrained, underdamped, non-collocated systems. JOURNAL OF VIBRATION AND CONTROL, 22(2), 549–558.
Vancouver
1.
Dutta A, Ionescu C-M, Loccufier M, De Keyser R. Robust Penalty Adaptive Model Predictive Control (PAMPC) of constrained, underdamped, non-collocated systems. JOURNAL OF VIBRATION AND CONTROL. Sage; 2016;22(2):549–58.
MLA
Dutta, Abhishek, Clara-Mihaela Ionescu, Mia Loccufier, et al. “Robust Penalty Adaptive Model Predictive Control (PAMPC) of Constrained, Underdamped, Non-collocated Systems.” JOURNAL OF VIBRATION AND CONTROL 22.2 (2016): 549–558. Print.