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Design of predictive control systems with a disturbance estimation mechanism for motion control

Research Project

Project/Area Number 17K06233
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Dynamics/Control
Research InstitutionAkita Prefectural University

Principal Investigator

Satoh Toshiyuki  秋田県立大学, システム科学技術学部, 准教授 (40315635)

Co-Investigator(Kenkyū-buntansha) 齋藤 直樹  秋田県立大学, システム科学技術学部, 教授 (60315645)
Project Period (FY) 2017-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords機械力学・制御 / モデル予測制御 / 状態推定器 / 制御工学 / 外乱推定
Outline of Final Research Achievements

For the aim of motion control, we have studied on model precitive control strategies that have an ability to estimate and cancel disturbance without additive mechcanisms such as disturbance observer. Predictive Functional Control (PFC), which is a model predictive control (MPC), is mainly addressed in this research. Generally speaking, PFC does not require the state-estimator. However, to estimate disturbancce and cancel it indirectly, we intendedly introduced the prediction-type estimator as an internal model in PFC, constructed an augmented system, and derived the optimal control law. The PFC with such structure is abbreviated as PFC_EBIM. We applied PFC_EBIM to a position control problem of a mechatronics servo system. We experimentally confirmed that the designed PFC_EBIM efficiently estimated and canceled disturbance such as friction and improved the tracking performance.

Academic Significance and Societal Importance of the Research Achievements

ロボットやメカトロニクス機器のモーション・コントロールにおいて,位置や速度,力などの物理量を精度良く,かつ高速に制御する必要がある,このような制御を行おうとする場合には一般に,制御対象の精密な動力学モデルが必要となる.しかし,精密なモデルの構築には多大なコストが掛かる.本研究成果の意義は,こうしたコストを低減化し,産業的に主流となっているPID制御よりも高度なmモデルベースト制御手法を提供する点にある.また,制御工学的にも,主となるフィードバック補償器と外乱推定・除去メカニズムとを統合した設計法を開発することは意義がある.

Report

(5 results)
  • 2020 Annual Research Report   Final Research Report ( PDF )
  • 2019 Research-status Report
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (11 results)

All 2020 2019 2018 2017

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Open Access: 1 results) Presentation (9 results) (of which Int'l Joint Research: 4 results)

  • [Journal Article] Predictive Functional Control of an Axis Positioning System with an Estimator-based Internal Model2019

    • Author(s)
      Toshiyuki Satoh, Naoki Saito, Jun-ya Nagase and Norihiko Saga
    • Journal Title

      Control Engineering Practice

      Volume: 86 Pages: 1-10

    • DOI

      10.1016/j.conengprac.2019.02.006

    • Related Report
      2018 Research-status Report
    • Peer Reviewed
  • [Journal Article] Improvement of tracking performance of disturbance observer-based predictive functional control systems using zero phase error tracking controller2017

    • Author(s)
      佐藤 俊之,永瀬 純也,嵯峨 宜彦,齋藤 直樹
    • Journal Title

      Transactions of the JSME (in Japanese)

      Volume: 83 Issue: 853 Pages: 17-00142-17-00142

    • DOI

      10.1299/transjsme.17-00142

    • NAID

      130006100031

    • ISSN
      2187-9761
    • Related Report
      2017 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] 人工蜂コロニーアルゴリズムを用いた未知入力推定器の設計2020

    • Author(s)
      西澤 舜,佐藤 俊之,齋藤 直樹,嵯峨 宣彦,永瀬 純也
    • Organizer
      日本機械学会 ロボティクス・メカトロニクス講演会講演論文集
    • Related Report
      2020 Annual Research Report
  • [Presentation] Design of Unknown Input Estimator with Artificial Bee Colony Algorithm2020

    • Author(s)
      Toshiyuki Satoh, Shun Nishizawa, Naoki Saito Jun-ya Nagase and Norihiko Saga
    • Organizer
      Annual Conference of the IEEE Industrial Electronics Society
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Performance Improvement of Predictive Functional Control with a State Estimator-based Internal Model2019

    • Author(s)
      Toshiyuki Satoh, Naoki Saito, Jun-ya Nagase, Norihiko Saga
    • Organizer
      IEEE 15th International Conference on Automation Science and Engineerin
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] 状態推定器を内部モデルに用いるPredictive Functional Controlの評価実験と既存手法との比較2019

    • Author(s)
      佐藤 俊之,齋藤 直樹,永瀬 純也,嵯峨 宣彦
    • Organizer
      日本機械学会 ロボティクス・メカトロニクス講演会
    • Related Report
      2019 Research-status Report
  • [Presentation] 状態観測器を内部モデルに用いるPredictive Functional Controlに基づくサーボ系設計2018

    • Author(s)
      佐藤 俊之,永瀬 純也,嵯峨 宣彦,齋藤 直樹
    • Organizer
      日本機械学会 ロボティクス・メカトロニクス講演会
    • Related Report
      2018 Research-status Report
  • [Presentation] Performance Enhancement of Predictive Functional Control Using Disturbance Observer and Zero Phase Error Tracking Controller2018

    • Author(s)
      Toshiyuki Satoh, Naoki Saito, Jun-ya Nagase and Norihiko Saga
    • Organizer
      International Conference on Control, Automation, Robotics and Vision
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] 状態推定器を内部モデルに用いるPredictive Functional Controlの実験的評価2018

    • Author(s)
      西村 旭正,佐藤 俊之,齋藤 直樹
    • Organizer
      日本機械学会東北支部第53期総会・講演会
    • Related Report
      2017 Research-status Report
  • [Presentation] 2リンク・マニピュレータのUncertainty and Disturbance Estimatorに基づく制御2017

    • Author(s)
      大森 達哉,佐藤 俊之,齋藤 直樹,嵯峨 宣彦,永瀬 純也
    • Organizer
      日本機械学会 ロボティクス・メカトロニクス講演会
    • Related Report
      2017 Research-status Report
  • [Presentation] An Application of Predictive Functional Control with a State Observer-Type Internal Model2017

    • Author(s)
      Toshiyuki Satoh, Naoki Saito, Jun-ya Nagase and Norihiko Saga
    • Organizer
      International Conference on Mechatronics and Machine Vision in Practice
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research

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Published: 2017-04-28   Modified: 2022-01-27  

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