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Software-based optimal PID design with robustness and noise sensitivity constraints

Garpinger, Olof LU and Hägglund, Tore LU (2015) In Journal of Process Control 33(9). p.90-101
Abstract
Even though PID control has been available for a long time, there are still no tuning methods including derivative action that have gained wide acceptance in industry. Also, there is still no general consensus for when one should use PID, PI or even I control on a process. The focus of this article is to present a new method for optimal PID control design that automatically picks the best controller type for the process at hand. The proposed PID design procedure uses a software-based method to find controllers with optimal or near optimal load disturbance response subject to robustness and noise sensitivity constraints. It is shown that the optimal controller type depends on maximum allowed noise sensitivity as well as process dynamics.... (More)
Even though PID control has been available for a long time, there are still no tuning methods including derivative action that have gained wide acceptance in industry. Also, there is still no general consensus for when one should use PID, PI or even I control on a process. The focus of this article is to present a new method for optimal PID control design that automatically picks the best controller type for the process at hand. The proposed PID design procedure uses a software-based method to find controllers with optimal or near optimal load disturbance response subject to robustness and noise sensitivity constraints. It is shown that the optimal controller type depends on maximum allowed noise sensitivity as well as process dynamics. The design procedure thus results in a set of PID, PI and I controllers with different noise filters that the user can switch between to reach an acceptable control signal activity. The software is also used to compare PI and PID control performance with equivalent noise sensitivity and robustness over a large batch of processes representative for the process industry. This can be used to show how much a particular process benefits from using the derivative part. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Software tools, PID control, Optimization, Measurement noise, Control system design
in
Journal of Process Control
volume
33
issue
9
pages
90 - 101
publisher
Elsevier
external identifiers
  • wos:000361934900008
  • scopus:84936876552
ISSN
1873-2771
DOI
10.1016/j.jprocont.2015.06.001
language
English
LU publication?
yes
id
c2d0b50f-d749-46c3-bbd2-d68c9f949b49 (old id 7651523)
date added to LUP
2015-08-03 09:01:20
date last changed
2017-10-29 03:02:40
@article{c2d0b50f-d749-46c3-bbd2-d68c9f949b49,
  abstract     = {Even though PID control has been available for a long time, there are still no tuning methods including derivative action that have gained wide acceptance in industry. Also, there is still no general consensus for when one should use PID, PI or even I control on a process. The focus of this article is to present a new method for optimal PID control design that automatically picks the best controller type for the process at hand. The proposed PID design procedure uses a software-based method to find controllers with optimal or near optimal load disturbance response subject to robustness and noise sensitivity constraints. It is shown that the optimal controller type depends on maximum allowed noise sensitivity as well as process dynamics. The design procedure thus results in a set of PID, PI and I controllers with different noise filters that the user can switch between to reach an acceptable control signal activity. The software is also used to compare PI and PID control performance with equivalent noise sensitivity and robustness over a large batch of processes representative for the process industry. This can be used to show how much a particular process benefits from using the derivative part.},
  author       = {Garpinger, Olof and Hägglund, Tore},
  issn         = {1873-2771},
  keyword      = {Software tools,PID control,Optimization,Measurement noise,Control system design},
  language     = {eng},
  number       = {9},
  pages        = {90--101},
  publisher    = {Elsevier},
  series       = {Journal of Process Control},
  title        = {Software-based optimal PID design with robustness and noise sensitivity constraints},
  url          = {http://dx.doi.org/10.1016/j.jprocont.2015.06.001},
  volume       = {33},
  year         = {2015},
}