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An automatic tuner with short experiment and probabilistic plant parameterization

Soltesz, Kristian LU ; Mercader, Pedro and Baños, Alfonso (2016) In Int. Journal of Robust and Nonlinear Control
Abstract
A novel automatic tuning strategy is proposed. It is based on an experiment of very short duration, followed by simultaneous identification of LTI model parameters and an estimate of their error covariance. The parametric uncertainty model is subsequently exploited to design linear controllers with magnitude bounds on some closed-loop transfer function of interest, such as the sensitivity function. The method is demonstrated through industrially relevant examples. Robustness is enforced through probabilistic constraints on the H∞ norms of the sensitivity function, while minimizing load disturbance integral error (IE) to ensure performance. To demonstrate the strength of the proposed method, identification for the mentioned examples is... (More)
A novel automatic tuning strategy is proposed. It is based on an experiment of very short duration, followed by simultaneous identification of LTI model parameters and an estimate of their error covariance. The parametric uncertainty model is subsequently exploited to design linear controllers with magnitude bounds on some closed-loop transfer function of interest, such as the sensitivity function. The method is demonstrated through industrially relevant examples. Robustness is enforced through probabilistic constraints on the H∞ norms of the sensitivity function, while minimizing load disturbance integral error (IE) to ensure performance. To demonstrate the strength of the proposed method, identification for the mentioned examples is carried out under a high level of measurement noise. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Automatic tuning, robust identification, parametric uncertainty, uncertainty propagation
in
Int. Journal of Robust and Nonlinear Control
pages
20 pages
external identifiers
  • Scopus:84992189565
DOI
10.1002/rnc.3640
language
English
LU publication?
yes
id
e38e43cb-7c93-4574-b49a-ce1118446137
date added to LUP
2016-08-18 17:39:53
date last changed
2016-11-20 04:35:13
@misc{e38e43cb-7c93-4574-b49a-ce1118446137,
  abstract     = {A novel automatic tuning strategy is proposed. It is based on an experiment of very short duration, followed by simultaneous identification of LTI model parameters and an estimate of their error covariance. The parametric uncertainty model is subsequently exploited to design linear controllers with magnitude bounds on some closed-loop transfer function of interest, such as the sensitivity function. The method is demonstrated through industrially relevant examples. Robustness is enforced through probabilistic constraints on the H∞ norms of the sensitivity function, while minimizing load disturbance integral error (IE) to ensure performance. To demonstrate the strength of the proposed method, identification for the mentioned examples is carried out under a high level of measurement noise.},
  author       = {Soltesz, Kristian and Mercader, Pedro and Baños, Alfonso},
  keyword      = {Automatic tuning,robust identification,parametric uncertainty,uncertainty propagation},
  language     = {eng},
  pages        = {20},
  series       = {Int. Journal of Robust and Nonlinear Control},
  title        = {An automatic tuner with short experiment and probabilistic plant parameterization},
  url          = {http://dx.doi.org/10.1002/rnc.3640},
  year         = {2016},
}