リニアスライダの位置決め制御系に対するフィードバック誤差学習の一実装法

Yukinori Nakamura, Kazuki Morimoto, Shinji Wakui

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper considers implementation of feedback error learning (FEL) for linear slider position control. The effect of modelling error of the slider is compensated by FEL. In algorithm of FEL, parameters of feedforward controller are updated so that output signals of a feedback controller can become small. It leads to improvement of tracking performance. On the other hand, when conventional FEL algorithm is implemented for control of a linear slider, parameters of the feedforward controller tend to converge slowly. In industrial scenes, it is desirable to shorten learning time in order to reduce cost of setting up manufacturing devices. Furthermore, when the learning time is long, guide rails of the slider become worn. It is shown that convergence speed is improved by tuning free parameters of the feedforward controller. Due to further improvement of the convergence, by using prefilter and free parameters of feedforward controller, some parameters of an inverse system are obtained a priori and utilized for learning. Command with mixed frequency is selected in order to identify accurate inverse system of plant. Simulation results are presented to show the effectiveness of proposed method.

Original languageJapanese
Pages (from-to)3684-3693
Number of pages10
JournalNihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
Volume77
Issue number782
Publication statusPublished - 2011
Externally publishedYes

Keywords

  • Feedback error learning
  • Linear slider
  • Mechatronics
  • Positioning
  • Precision instrument

ASJC Scopus subject areas

  • Mechanical Engineering
  • Mechanics of Materials
  • Industrial and Manufacturing Engineering

Cite this

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title = "リニアスライダの位置決め制御系に対するフィードバック誤差学習の一実装法",
abstract = "This paper considers implementation of feedback error learning (FEL) for linear slider position control. The effect of modelling error of the slider is compensated by FEL. In algorithm of FEL, parameters of feedforward controller are updated so that output signals of a feedback controller can become small. It leads to improvement of tracking performance. On the other hand, when conventional FEL algorithm is implemented for control of a linear slider, parameters of the feedforward controller tend to converge slowly. In industrial scenes, it is desirable to shorten learning time in order to reduce cost of setting up manufacturing devices. Furthermore, when the learning time is long, guide rails of the slider become worn. It is shown that convergence speed is improved by tuning free parameters of the feedforward controller. Due to further improvement of the convergence, by using prefilter and free parameters of feedforward controller, some parameters of an inverse system are obtained a priori and utilized for learning. Command with mixed frequency is selected in order to identify accurate inverse system of plant. Simulation results are presented to show the effectiveness of proposed method.",
keywords = "Feedback error learning, Linear slider, Mechatronics, Positioning, Precision instrument",
author = "Yukinori Nakamura and Kazuki Morimoto and Shinji Wakui",
year = "2011",
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journal = "Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C",
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AU - Nakamura, Yukinori

AU - Morimoto, Kazuki

AU - Wakui, Shinji

PY - 2011

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N2 - This paper considers implementation of feedback error learning (FEL) for linear slider position control. The effect of modelling error of the slider is compensated by FEL. In algorithm of FEL, parameters of feedforward controller are updated so that output signals of a feedback controller can become small. It leads to improvement of tracking performance. On the other hand, when conventional FEL algorithm is implemented for control of a linear slider, parameters of the feedforward controller tend to converge slowly. In industrial scenes, it is desirable to shorten learning time in order to reduce cost of setting up manufacturing devices. Furthermore, when the learning time is long, guide rails of the slider become worn. It is shown that convergence speed is improved by tuning free parameters of the feedforward controller. Due to further improvement of the convergence, by using prefilter and free parameters of feedforward controller, some parameters of an inverse system are obtained a priori and utilized for learning. Command with mixed frequency is selected in order to identify accurate inverse system of plant. Simulation results are presented to show the effectiveness of proposed method.

AB - This paper considers implementation of feedback error learning (FEL) for linear slider position control. The effect of modelling error of the slider is compensated by FEL. In algorithm of FEL, parameters of feedforward controller are updated so that output signals of a feedback controller can become small. It leads to improvement of tracking performance. On the other hand, when conventional FEL algorithm is implemented for control of a linear slider, parameters of the feedforward controller tend to converge slowly. In industrial scenes, it is desirable to shorten learning time in order to reduce cost of setting up manufacturing devices. Furthermore, when the learning time is long, guide rails of the slider become worn. It is shown that convergence speed is improved by tuning free parameters of the feedforward controller. Due to further improvement of the convergence, by using prefilter and free parameters of feedforward controller, some parameters of an inverse system are obtained a priori and utilized for learning. Command with mixed frequency is selected in order to identify accurate inverse system of plant. Simulation results are presented to show the effectiveness of proposed method.

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KW - Mechatronics

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