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

Abhishek Dutta (UGent) , Clara-Mihaela Ionescu (UGent) , Mia Loccufier (UGent) and Robain De Keyser (UGent)
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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.
Keywords
Constrained, ALGORITHM, predictive control, optimal, robust

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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.
@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},
}

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