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sparse sensing for control theory

Research Project

Project/Area Number 19H02163
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 21040:Control and system engineering-related
Research InstitutionHosei University

Principal Investigator

Konishi Katsumi  法政大学, 情報科学部, 教授 (20339138)

Co-Investigator(Kenkyū-buntansha) 澤田 賢治  電気通信大学, i-パワードエネルギー・システム研究センター, 准教授 (80550946)
Project Period (FY) 2019-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥17,420,000 (Direct Cost: ¥13,400,000、Indirect Cost: ¥4,020,000)
Fiscal Year 2022: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2021: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2020: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2019: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Keywordsスパースモデリング / 圧縮センシング / スパース最適化 / 制御系設計
Outline of Research at the Start

本研究では、計測および制御対象から僅かな情報量のセンシングデータしか取得できない場合でも、十分な情報量が得られた場合と同じ精度のセンシングデータの再構成を可能とするスパースセンシング手法を制御系設計手法に展開する。「どの程度の情報量のセンシングデータが得られれば、どの程度のモデリング性能および制御性能が達成可能か?」という学術的問いに答えるための数理基盤を確立し、これに基づくスパースセンシング制御の体系化を目的とする。具体的には、数理モデルを確率密度関数として与え、これに基づく再構成されたデータの確からしさを与える手法を導出し、これらの再構成データと数理モデルに基づく制御系設計手法を確立する。

Outline of Final Research Achievements

This work proposed a method for designing control systems using sparse data when only a small amount of informative sensing data can be obtained from the measurement and control target. Specifically, we derived a sparse sensing method, a predictive control method using the derived method, and a fast computation method when the observed data belong to a nonlinear low-dimensional subspace.

Academic Significance and Societal Importance of the Research Achievements

本研究により、入出力データの全てが既知でない場合、部分的に欠損がある場合、不等間隔サンプリングデータである場合でも、入出力データを修復し再構成することで、制御形設計が可能となった。線形システムだけでなく、非線形システムにも対応した。システム生物学分野や、医療応用分野では、不等間隔サンプリングデータしか得られないことが多い。本研究により、これらの分野における数学モデルの構築や制御手法の導出などが可能となり、社会的意義は大きい。

Report

(5 results)
  • 2023 Final Research Report ( PDF )
  • 2022 Annual Research Report
  • 2021 Annual Research Report
  • 2020 Annual Research Report
  • 2019 Annual Research Report
  • Research Products

    (10 results)

All 2024 2023 2021 2020

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Open Access: 1 results) Presentation (8 results) (of which Int'l Joint Research: 5 results,  Invited: 1 results)

  • [Journal Article] An Acceleration Technique for Matrix Completion using Deep Unfolding2023

    • Author(s)
      Sasaki Ryohei、Naito Rin、Konishi Katsumi
    • Journal Title

      Transactions of the Institute of Systems, Control and Information Engineers

      Volume: 36 Issue: 4 Pages: 106-112

    • DOI

      10.5687/iscie.36.106

    • ISSN
      1342-5668, 2185-811X
    • Year and Date
      2023-04-15
    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Local low-rank approach to nonlinear matrix completion2021

    • Author(s)
      Sasaki Ryohei、Konishi Katsumi、Takahashi Tomohiro、Furukawa Toshihiro
    • Journal Title

      EURASIP Journal on Advances in Signal Processing

      Volume: 2021 Issue: 1 Pages: 1-21

    • DOI

      10.1186/s13634-021-00717-7

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Presentation] Adaptive Subspace Reconstruction Algorithm for Subspace Clustering2024

    • Author(s)
      Takuto Wada, Ryhohei Sasaki, Katsumi Konishi
    • Organizer
      Proc. of 2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Distributed Nuclear Norm Minimization Algorithm for Matrix Completion and Its Application to Signal Recovery of Piecewise Affine Models2023

    • Author(s)
      Katsumi Konishi, Ryhohei Sasaki
    • Organizer
      Proc. of The 49th Annual Conference of the IEEE Industrial Electronics Society
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Distributed Nuclear Norm Minimization Algorithm for Low-Rank Matrix Completion and Its Application to Low-Rank Tensor Completion2023

    • Author(s)
      Katsumi Konishi, Ryhohei Sasaki
    • Organizer
      Proc. of The 2023 IEEE Conference on Systems, Man, and Cybernetics
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] K-Means Based Matrix Shrinkage Iterative Algorithm for Input and Output Signal Recovery2023

    • Author(s)
      Takuto Wada, Ryhohei Sasaki, Katsumi Konishi
    • Organizer
      Proc. of the SICE Annual Conference
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 局所低ランク化に基づく行列補完の高速解法2021

    • Author(s)
      佐々木 亮平, 小西 克巳
    • Organizer
      第36回信号処理シンポジウム
    • Related Report
      2021 Annual Research Report
  • [Presentation] 行列補完のためのニューラルネットワークによる局所低ランク近似2021

    • Author(s)
      郭 斌, 佐々木 亮平, 小西 克巳
    • Organizer
      第36回信号処理シンポジウム
    • Related Report
      2021 Annual Research Report
  • [Presentation] Acceleration Technique for Multiple k-means Clustering based Locally Low-rank Approach to Nonlinear Matrix Completion2021

    • Author(s)
      Ryohei Sasaki, Katsumi Konishi
    • Organizer
      European Signal Processing Conference
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 行列完成問題のための行列ランク最小化と最尤推定2020

    • Author(s)
      小西克巳
    • Organizer
      信号処理研究会
    • Related Report
      2020 Annual Research Report
    • Invited

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Published: 2019-04-18   Modified: 2025-01-30  

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