Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors
Intelligent machines are capable of recognizing their operational condition and take actions towards optimality through an autonomous processing of information. Considering the importance of rotating machines in modern industry, this concept of intelligent machines can be applied to achieve high ava...
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2012-01-01
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Series: | International Journal of Rotating Machinery |
Online Access: | http://dx.doi.org/10.1155/2012/873645 |
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doaj-80eaa5642fc54890a444a97c1591529f2020-11-25T02:19:07ZengHindawi LimitedInternational Journal of Rotating Machinery1023-621X1542-30342012-01-01201210.1155/2012/873645873645Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible RotorsThiago Malta Buttini0Rodrigo Nicoletti1Department of Mechanical Engineering, School of Engineering of São Carlos, University of São Paulo, Trabalhador São-Carlense 400, 13566-590 São Carlos, SP, BrazilDepartment of Mechanical Engineering, School of Engineering of São Carlos, University of São Paulo, Trabalhador São-Carlense 400, 13566-590 São Carlos, SP, BrazilIntelligent machines are capable of recognizing their operational condition and take actions towards optimality through an autonomous processing of information. Considering the importance of rotating machines in modern industry, this concept of intelligent machines can be applied to achieve high availability, thus avoiding interruptions in the production flow. In this work, a self-identification algorithm is proposed for the autonomous decision and control of a flexible shaft rotating system with electromagnetic actuators. Based on the D-decomposition technique, the algorithm searches in the domain of controller gains the best ones for P and PD controllers to reduce maximum peak response of the shaft. For that, frequency response functions of the system are automatically identified experimentally by the algorithm. It is demonstrated that regions of stable gains can be easily plotted, and the most suitable gains can be found to minimize the resonant peak of the system in an autonomous way, without human intervention.http://dx.doi.org/10.1155/2012/873645 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Thiago Malta Buttini Rodrigo Nicoletti |
spellingShingle |
Thiago Malta Buttini Rodrigo Nicoletti Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors International Journal of Rotating Machinery |
author_facet |
Thiago Malta Buttini Rodrigo Nicoletti |
author_sort |
Thiago Malta Buttini |
title |
Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors |
title_short |
Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors |
title_full |
Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors |
title_fullStr |
Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors |
title_full_unstemmed |
Self-Identification Algorithm for the Autonomous Control of Lateral Vibration in Flexible Rotors |
title_sort |
self-identification algorithm for the autonomous control of lateral vibration in flexible rotors |
publisher |
Hindawi Limited |
series |
International Journal of Rotating Machinery |
issn |
1023-621X 1542-3034 |
publishDate |
2012-01-01 |
description |
Intelligent machines are capable of recognizing their operational condition and take actions towards optimality through an autonomous processing of information. Considering the importance of rotating machines in modern industry, this concept of intelligent machines can be applied to achieve high availability, thus avoiding interruptions in the production flow. In this work, a self-identification algorithm is proposed for the autonomous decision and control of a flexible shaft rotating system with electromagnetic actuators. Based on the D-decomposition technique, the algorithm searches in the domain of controller gains the best ones for P and PD controllers to reduce maximum peak response of
the shaft. For that, frequency response functions of the system are automatically identified experimentally by the algorithm. It is demonstrated that regions of stable gains can be easily plotted, and the most suitable gains can be found to minimize the resonant peak of the system in an autonomous way, without human intervention. |
url |
http://dx.doi.org/10.1155/2012/873645 |
work_keys_str_mv |
AT thiagomaltabuttini selfidentificationalgorithmfortheautonomouscontroloflateralvibrationinflexiblerotors AT rodrigonicoletti selfidentificationalgorithmfortheautonomouscontroloflateralvibrationinflexiblerotors |
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1724878350444396544 |