PI Controller for SISO Linear Systems based on Neural Linear PCA

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2 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 languageEnglish
Title of host publicationEuropean Control Conference, ECC 2014
PublisherIEEE
Pages2768-2773
DOIs
Publication statusPublished - 2014
Event13th European Control Conference -
Duration: 1 Jan 2014 → …

Conference

Conference13th European Control Conference
Period1/01/14 → …

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