Disturbance rejection in autotuners: an assessment method and a rule proposal
(2015) American Control Conference, 2015 p.2876-2881- Abstract
- Disturbance rejection is a primary objective in many industrial control loops, thus a relevant goal for autotuning controllers. Nonetheless, autotuning has invariantly to cope with a reduced amount of process information. As a consequence, with the standard single-loop structure typically adopted in the addressed context, effective disturbance rejection calls for strong feedback, and therefore the solutions available to date fall sometimes short of perfection. This paper discusses the matter basically from a methodological standpoint, evidencing some structural reasons for the observed shortcomings. The result is a synthesis approach improving rejection performance with respect to existing and well established tuning rules, on a rigorously... (More)
- Disturbance rejection is a primary objective in many industrial control loops, thus a relevant goal for autotuning controllers. Nonetheless, autotuning has invariantly to cope with a reduced amount of process information. As a consequence, with the standard single-loop structure typically adopted in the addressed context, effective disturbance rejection calls for strong feedback, and therefore the solutions available to date fall sometimes short of perfection. This paper discusses the matter basically from a methodological standpoint, evidencing some structural reasons for the observed shortcomings. The result is a synthesis approach improving rejection performance with respect to existing and well established tuning rules, on a rigorously sound basis. Simulation examples are presented to support the proposal. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/5152961
- author
- Leva, Alberto and Papadopoulos, Alessandro Vittorio LU
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- American Control Conference (ACC), 2015
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- American Control Conference, 2015
- conference location
- Chicago, IL, United States
- conference dates
- 2015-07-01 - 2015-07-03
- external identifiers
-
- scopus:84940916530
- ISBN
- 978-1-4799-8684-2
- DOI
- 10.1109/ACC.2015.7171171
- project
- EIT_VR CLOUD Cloud Control
- language
- English
- LU publication?
- yes
- additional info
- To appear, accepted for publication.
- id
- bb2349a5-524d-4c8b-8826-b40c5410e496 (old id 5152961)
- date added to LUP
- 2016-04-04 11:58:48
- date last changed
- 2024-04-13 18:51:20
@inproceedings{bb2349a5-524d-4c8b-8826-b40c5410e496, abstract = {{Disturbance rejection is a primary objective in many industrial control loops, thus a relevant goal for autotuning controllers. Nonetheless, autotuning has invariantly to cope with a reduced amount of process information. As a consequence, with the standard single-loop structure typically adopted in the addressed context, effective disturbance rejection calls for strong feedback, and therefore the solutions available to date fall sometimes short of perfection. This paper discusses the matter basically from a methodological standpoint, evidencing some structural reasons for the observed shortcomings. The result is a synthesis approach improving rejection performance with respect to existing and well established tuning rules, on a rigorously sound basis. Simulation examples are presented to support the proposal.}}, author = {{Leva, Alberto and Papadopoulos, Alessandro Vittorio}}, booktitle = {{American Control Conference (ACC), 2015}}, isbn = {{978-1-4799-8684-2}}, language = {{eng}}, pages = {{2876--2881}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Disturbance rejection in autotuners: an assessment method and a rule proposal}}, url = {{https://lup.lub.lu.se/search/files/5899384/5152964.pdf}}, doi = {{10.1109/ACC.2015.7171171}}, year = {{2015}}, }