PI Controller for SISO Linear Systems based on Neural Linear PCA

Luís Filipe Figueira de Brito Palma; Fernando José Almeida Vieira do Coito; Paulo José Carrilho de Sousa Gil

doi:10.1109/ECC.2014.6862604

PI Controller for SISO Linear Systems based on Neural Linear PCA

Luís Filipe Figueira de Brito Palma, Fernando José Almeida Vieira do Coito, Paulo José Carrilho de Sousa Gil

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

In this paper an approach to design proportional integral (PI) controllers, for SISO systems, based on neural linear principal components analysis (PCA) is presented. Closed loop control can be formulated and implemented within the reduced space defined by a PCA model. The neural linear PCA controller, results in an integral controller, which can be used as an inferential controller. The main contributions of the paper are: a) the proposed architecture with a classical proportional controller and a neural integral controller based on linear neural PCA; b) the evaluation of the controller performance using the Harris index. Some experimental results obtained with a DC motor linear model are presented, showing the controller performance.

Original language	English
Title of host publication	European Control Conference, ECC 2014
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	2768-2773
DOIs	https://doi.org/10.1109/ECC.2014.6862604
Publication status	Published - 2014
Event	13th European Control Conference - Duration: 1 Jan 2014 → …

Conference

Conference	13th European Control Conference
Period	1/01/14 → …

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@inproceedings{d0264ef98c274f4fb2ff53fa734163e0,

title = "PI Controller for SISO Linear Systems based on Neural Linear PCA",

abstract = "In this paper an approach to design proportional integral (PI) controllers, for SISO systems, based on neural linear principal components analysis (PCA) is presented. Closed loop control can be formulated and implemented within the reduced space defined by a PCA model. The neural linear PCA controller, results in an integral controller, which can be used as an inferential controller. The main contributions of the paper are: a) the proposed architecture with a classical proportional controller and a neural integral controller based on linear neural PCA; b) the evaluation of the controller performance using the Harris index. Some experimental results obtained with a DC motor linear model are presented, showing the controller performance.",

author = "Palma, {Lu{\'i}s Filipe Figueira de Brito} and Coito, {Fernando Jos{\'e} Almeida Vieira do} and Gil, {Paulo Jos{\'e} Carrilho de Sousa}",

year = "2014",

doi = "10.1109/ECC.2014.6862604",

language = "English",

pages = "2768--2773",

booktitle = "European Control Conference, ECC 2014",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "13th European Control Conference ; Conference date: 01-01-2014",

}

PI Controller for SISO Linear Systems based on Neural Linear PCA. / Palma, Luís Filipe Figueira de Brito ; Coito, Fernando José Almeida Vieira do ; Gil, Paulo José Carrilho de Sousa.
European Control Conference, ECC 2014. Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 2768-2773.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - PI Controller for SISO Linear Systems based on Neural Linear PCA

AU - Palma, Luís Filipe Figueira de Brito

AU - Coito, Fernando José Almeida Vieira do

AU - Gil, Paulo José Carrilho de Sousa

PY - 2014

Y1 - 2014

N2 - In this paper an approach to design proportional integral (PI) controllers, for SISO systems, based on neural linear principal components analysis (PCA) is presented. Closed loop control can be formulated and implemented within the reduced space defined by a PCA model. The neural linear PCA controller, results in an integral controller, which can be used as an inferential controller. The main contributions of the paper are: a) the proposed architecture with a classical proportional controller and a neural integral controller based on linear neural PCA; b) the evaluation of the controller performance using the Harris index. Some experimental results obtained with a DC motor linear model are presented, showing the controller performance.

AB - In this paper an approach to design proportional integral (PI) controllers, for SISO systems, based on neural linear principal components analysis (PCA) is presented. Closed loop control can be formulated and implemented within the reduced space defined by a PCA model. The neural linear PCA controller, results in an integral controller, which can be used as an inferential controller. The main contributions of the paper are: a) the proposed architecture with a classical proportional controller and a neural integral controller based on linear neural PCA; b) the evaluation of the controller performance using the Harris index. Some experimental results obtained with a DC motor linear model are presented, showing the controller performance.

U2 - 10.1109/ECC.2014.6862604

DO - 10.1109/ECC.2014.6862604

M3 - Conference contribution

SP - 2768

EP - 2773

BT - European Control Conference, ECC 2014

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 13th European Control Conference

Y2 - 1 January 2014

ER -

PI Controller for SISO Linear Systems based on Neural Linear PCA

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