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A study on fast and stable power conversion control with hybrid model predictive control and machine learning

Research Project

Project/Area Number 19K04355
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 21010:Power engineering-related
Research InstitutionNagasaki University

Principal Investigator

Maruta Hidenori  長崎大学, 工学研究科, 准教授 (00363474)

Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
KeywordsDC-DCコンバータ / 電力変換器 / ディジタル制御 / モデル予測制御
Outline of Research at the Start

本研究では,電力変換器を対象に,安定性と高速応答という2つの相反する性能を同時に改善可能とする新しいディジタル制御手法の提案を行う。電力変換器およびその制御系をハイブリッドシステムとみなし,モデル予測制御を採用する。また,MPCでは対応が難しい急激な変動などへの高速応答について,機械学習を含む極めて非線形性の高い予測制御を組み合わせることで,高速・安定な制御手法を構築する。

Outline of Final Research Achievements

In this research, we developed a novel control method using model predictive control and machine learning control for power converters which is treated and modeled as a hybrid system. Model predictive control can realize flexible functions under some constrained conditions, however, it requires heavy computation burden for its optimization problem. We addressed it by developing combinatorial enumeration-based computation and dynamic quantization to obtain pseudo optimal solution. In addition, we also adopted a neural network control to improve transient characteristics combined with model predictive control. The proposed method can obtain superior characteristics both in steady state and transient state simultaneously.

Academic Significance and Societal Importance of the Research Achievements

電力変換器の制御において、柔軟な制御手法であるモデル予測制御とニューラルネットワーク制御を組み合わせることで、安定性と応答性を両立することが可能な手法を開発した。また、提案手法では、制御における演算量を考慮し、制御器の性能に応じて演算コストと制御精度のトレードオフが可能であるため、比較的容易に提案手法を導入することが可能となることが期待できる。

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (13 results)

All 2021 2020 2019

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (11 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Stabilization Improvement of MPC based DC-DC Converter with Load Estimation2020

    • Author(s)
      Umeno Naoto、Maruta Hidenori
    • Journal Title

      Proc. 2020 9th International Conference on Renewable Energy Research and Application (ICRERA)

      Volume: 1 Pages: 295-300

    • DOI

      10.1109/icrera49962.2020.9242837

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] A Study on Effect of Dynamic Quantized Resolution on MPC Based DC-DC Converter with Combinatorial Optimization2020

    • Author(s)
      Taguchi Koya、Maruta Hidenori
    • Journal Title

      Proc. 2020 9th International Conference on Renewable Energy Research and Application (ICRERA)

      Volume: 1 Pages: 289-294

    • DOI

      10.1109/icrera49962.2020.9242872

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Presentation] Parameter Estimation of DC-DC Converters for Failure Detection Based on Linear Approximation Model2021

    • Author(s)
      T. Kimura and H. Maruta
    • Organizer
      2021 IEEE 30th International Symposium on Industrial Electronics
    • Related Report
      2021 Annual Research Report
  • [Presentation] Stabilization Improvement of MPC based DC-DC Converter with Load Estimation2020

    • Author(s)
      Umeno Naoto、Maruta Hidenori
    • Organizer
      ICRERA2020
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] A Study on Effect of Dynamic Quantized Resolution on MPC Based DC-DC Converter with Combinatorial Optimization2020

    • Author(s)
      Taguchi Koya、Maruta Hidenori
    • Organizer
      ICRERA2020
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] モデル予測制御と PI 制御を併用した DC-DC コンバータの過渡応答改善に関する検討2019

    • Author(s)
      田口孝哉・野田侑也・丸田英徳
    • Organizer
      電気学会2019年産業応用部門大会
    • Related Report
      2019 Research-status Report
  • [Presentation] 組み合わせ的最適化手法による DC-DC コンバータのモデル予測制御のスタートアップ特性評価2019

    • Author(s)
      野田侑矢・田口孝哉・丸田英徳
    • Organizer
      電気学会2019年産業応用部門大会
    • Related Report
      2019 Research-status Report
  • [Presentation] ニューラルネットワークの切り替えを用いた基準値修正方式 DC-DC コンバータの過渡特性の検討2019

    • Author(s)
      星野大樹・丸田英徳
    • Organizer
      電気学会2019年産業応用部門大会
    • Related Report
      2019 Research-status Report
  • [Presentation] 組み合わせ的最適化手法によるDC-DCコンバータのモデル予測制御の検討2019

    • Author(s)
      野田侑矢・丸田英徳
    • Organizer
      電子情報通信学会技術研究報告(電子通信エネルギー技術EE)
    • Related Report
      2019 Research-status Report
  • [Presentation] 推定電流を用いたニューラルネットワーク基準値修正方式DC-DCコンバータの過渡特性改善2019

    • Author(s)
      星野大樹・丸田英徳
    • Organizer
      電子情報通信学会技術研究報告(電子通信エネルギー技術EE)
    • Related Report
      2019 Research-status Report
  • [Presentation] モデル予測制御の予測ホライズンステップ数の違いによるディジタル制御DC-DCコンバータの特性評価2019

    • Author(s)
      野田侑矢・田口孝哉・丸田英徳
    • Organizer
      電子情報通信学会技術研究報告(電子通信エネルギー技術EE)
    • Related Report
      2019 Research-status Report
  • [Presentation] A Study on Model Based Control of DC-DC Converter with Simple Enumeration and Pruning Restriction Computation2019

    • Author(s)
      Yuya Noda, Maruta Hidenori
    • Organizer
      IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
    • Related Report
      2019 Research-status Report
  • [Presentation] Transient Response Improvement of Repetitive-trained Neural Network Controlled DC-DC Converter with Overcompensation Suppression2019

    • Author(s)
      Maruta Hidenori, Hoshino Daiki
    • Organizer
      IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
    • Related Report
      2019 Research-status Report

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Published: 2019-04-18   Modified: 2023-01-30  

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