| Project/Area Number |
18K04208
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 21040:Control and system engineering-related
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| Research Institution | Oita University |
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Principal Investigator |
Suemitsu Haruo 大分大学, 理工学部, 客員研究員 (50162839)
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| Co-Investigator(Kenkyū-buntansha) |
小西 忠司 大分大学, 減災・復興デザイン教育研究センター, 客員教授 (00225468)
星野 修 茨城大学, 理工学研究科(工学野), 教授 (00303016)
松尾 孝美 大分大学, 理工学部, 教授 (90181700)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | CAM plants / circadian rhythms / real-time optimization / momentum method / CAM植物 / 概日リズム / 信号分離 / 適応微分推定器 / 多変数最適化 / CAM光合成 / リアルタイム最適化手法 / 最適化手法 / ショ糖ホメオスタシス / 光合成 / マルチカーネル線形予測モデル / CAM型光合成 / 細胞振動子 |
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| Outline of Final Research Achievements |
In this research, the momentum method using the adaptive differential filter is extended for a measurement-based optimization of an objective function with multivariable decision variables. Thus, we propose a switching optimizer with single variable optimizers to obtain the partial derivatives of the objective function. To evaluate the performance of the switching optimizer, we perform a numerical simulation of a time-varying quadratic objective function in two decision variables. Finally, we apply the proposed switching optimizer to the signal separation problem of the CAM plant. Our main contribution in this paper is to propose a switching law that allows us to apply the adaptive velocity estimator to estimate a gradient with respect to multiple decision variables. The simulation results of the time-varying quadratic objective function and the signal separation problem of the CO2 uptake show the switching optimizer converges to the optimal decision parameters.
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| Academic Significance and Societal Importance of the Research Achievements |
CAM植物とよばれる植物は乾燥環境に適応した光合成機構を備えるため,これらの制御法の確立により砂漠の緑化や食料生産の最大化，二酸化炭素削減効果,植物工場の実現などが期待されている.本研究ではCAM植物制御に必要な,植物の外気からのCO2取り込み量に関して,その信号分離問題と精密な計測のための植物実験装置の構築した．さらに，細胞同期の状態を検証するために，データ駆動型最適化器を提案した．
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