Setting controller parameters through a minimum strategy with a weighted least squares method

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Setting controller parameters through a minimum strategy with a weighted least squares method. / Mercorelli, Paolo.
In: International Journal of Pure and Applied Mathematics, Vol. 86, No. 2, 19.07.2013, p. 457-463.

Research output: Journal contributionsJournal articlesResearchpeer-review

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@article{bdd1145c9d0640c6be5d761476a35398,
title = "Setting controller parameters through a minimum strategy with a weighted least squares method",
abstract = "This paper presents a feasible real time self-tuning of a controller. The main contribution of this paper consists of presenting a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. Robustness in the proposed loop control is achieved. For that the technique is quite general and can be applied to any kind of system.",
keywords = "Mathematics, Computational methods, Least squares method, Linear regression, Engineering",
author = "Paolo Mercorelli",
year = "2013",
month = jul,
day = "19",
doi = "10.12732/ijpam.v86i2.18",
language = "English",
volume = "86",
pages = "457--463",
journal = "International Journal of Pure and Applied Mathematics",
issn = "1311-8080",
publisher = "Academic Publications Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Setting controller parameters through a minimum strategy with a weighted least squares method

AU - Mercorelli, Paolo

PY - 2013/7/19

Y1 - 2013/7/19

N2 - This paper presents a feasible real time self-tuning of a controller. The main contribution of this paper consists of presenting a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. Robustness in the proposed loop control is achieved. For that the technique is quite general and can be applied to any kind of system.

AB - This paper presents a feasible real time self-tuning of a controller. The main contribution of this paper consists of presenting a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. Robustness in the proposed loop control is achieved. For that the technique is quite general and can be applied to any kind of system.

KW - Mathematics

KW - Computational methods

KW - Least squares method

KW - Linear regression

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=84880859547&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/7ed18113-2473-319e-bce4-674d4f24e71f/

U2 - 10.12732/ijpam.v86i2.18

DO - 10.12732/ijpam.v86i2.18

M3 - Journal articles

VL - 86

SP - 457

EP - 463

JO - International Journal of Pure and Applied Mathematics

JF - International Journal of Pure and Applied Mathematics

SN - 1311-8080

IS - 2

ER -

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