Exploring the trade-off between processing resources and settling time in image-based control through LQR tuning

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Abstract

Image-Based control systems extract information by a camera and an image processing algorithm. The challenge of such controllers is that the sensing latency deteriorates the control performance. Multi-core technology can be used to implement the sensing algorithm in a pipelined fashion. More processing resources potentially lead to better settling time. This results in a trade-off between resources and per-formance. We present a method to analyse this trade-off.

Original languageEnglish
Title of host publication32nd Annual ACM Symposium on Applied Computing, SAC 2017
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages1456-1459
Number of pages4
ISBN (Electronic)978-1-4503-4486-9
DOIs
Publication statusPublished - 3 Apr 2017
Event32nd ACM Symposium on Applied Computing (SAC 2017) - Cadi Ayyad University (UCA) of Marrakesh, Morocco, Marrakesh, Morocco
Duration: 4 Apr 20176 Apr 2017
Conference number: 32
https://www.sigapp.org/sac/sac2017/

Conference

Conference32nd ACM Symposium on Applied Computing (SAC 2017)
Abbreviated titleSAC 2017
CountryMorocco
CityMarrakesh
Period4/04/176/04/17
Internet address

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Keywords

  • Image-based control
  • LQR tuning
  • Particle warm Optimization
  • Pipelined sensing control
  • Trade-off analysis

Cite this

Medina, R., Stuijk, S., Goswami, D., & Basten, T. (2017). Exploring the trade-off between processing resources and settling time in image-based control through LQR tuning. In 32nd Annual ACM Symposium on Applied Computing, SAC 2017 (pp. 1456-1459). New York: Association for Computing Machinery, Inc. https://doi.org/10.1145/3019612.3019862