Updated on 2025/09/25

写真a

 
SASAKI Yasuo
 
Organization
Graduate School of Engineering Aerospace Engineering 3 Assistant Professor
Graduate School
Graduate School of Engineering
Undergraduate School
School of Engineering Mechanical and Aerospace Engineering
Title
Assistant Professor
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Research Interests 2

  1. Fluid control

  2. Optimization of sensor/actuator positions

Research Areas 1

  1. Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Control and systems engineering

Current Research Project and SDGs 1

  1. Nonlinear Optimal Control of Fluid Fields Using Machine Learning

Research History 5

  1. Nagoya University   Department of Aerospace Engineering, Graduate School of Engineering   Assistant Professor

    2024.12

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  2. Nagoya University   Department of Aerospace Engineering Graduate School of Engineering   Project Assistant Professor

    2023.11 - 2024.11

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    Country:Japan

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  3. Tohoku University   Department of Aerospace Engineering, Graduate School of Engineering   Project Assistant Professor

    2022.10 - 2023.10

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    Country:Japan

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  4. Tohoku University   Department of Aerospace Engineering, Graduate School of Engineering   JSPS Research Fellowship for Young Scientists (DC2)

    2022.5 - 2022.9

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    Country:Japan

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  5. Nagoya University   Department of Aerospace Engineering, Graduate School of Engineering   JSPS Research Fellowship for Young Scientists (DC2)

    2021.4 - 2022.4

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    Country:Japan

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Education 2

  1. Nagoya University   Graduate School of Engineering   Department of Aerospace Engineering

    2019.4 - 2022.4

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    Country: Japan

    Notes: Doctoral course

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  2. Nagoya University   Graduate School of Engineering   Department of Aerospace Engineering

    2017.4 - 2019.3

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    Country: Japan

    Notes: Master's course

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Professional Memberships 3

  1. 計測自動制御学会

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  2. 日本航空宇宙学会

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  3. システム制御情報学会

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Committee Memberships 2

  1. 計測自動制御学会 中部支部 運営委員会   庶務幹事  

    2025.1   

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    Committee type:Academic society

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  2. 自動制御連合講演会 実行委員会   庶務幹事  

    2024.12   

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    Committee type:Academic society

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Awards 4

  1. 計測自動制御学会 学術奨励賞 (研究奨励賞)

    2024.3   大規模な線形時変システムに対する特異値分解を利用した最適アクチュエータ選択ーLorenz 96モデルへの適用ー

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  2. システム制御情報学会 奨励賞

    2022.5   フルオーダ制御器を利用した流れ場のための低次元制御器設計

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  3. 第64回自動制御連合講演会 優秀発表賞

    2021.11   フルオーダ制御器を利用した流れ場のための低次元制御器設計

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  4. SICE Annual Conference Young Author’s Award

    2020.9   SICE   Design of Observers for the Flow around a Cylinder using Machine Learning Techniques

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Papers 11

  1. Enhancing reduced-order modeling using dynamic mode decomposition for two-phase flows through level set functions

    Hosaka, T; Ishii, E; Sasaki, Y; Nonomura, T

    JOURNAL OF OCEAN ENGINEERING AND MARINE ENERGY   Vol. 11 ( 3 ) page: 525 - 542   2025.8

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    Publisher:Journal of Ocean Engineering and Marine Energy  

    This paper focuses on the issue of accuracy degradation when directly constructing a reduced-order model (ROM) using dynamic mode decomposition for a volume of fluid (VOF) field of two-phase flow simulations, and proposes a improved method that utilizes the signed distance function (SDF), also known as the level set function, with respect to the gas–liquid interface. The effectiveness of the proposed method was demonstrated by applying it to sloshing tank problems under two different conditions. The oscillation modes were observed to appear only near the interface when using the VOF field directly; however, the influence of the interface is alleviated over a larger distance, resulting in smoother oscillation and improved performance of the ROM when employing the level set function. The results show that ROM for a level set function in cases with small oscillation was shown to be effectively equivalent to that for one-dimensionalized interface. Moreover, the ROM of the level set function could reproduce the physics of this phenomenon with higher accuracy than that of the VOF fields in the cases where one dimensionalization is not possible, such as when the liquid inside the tank surges and climbs up to the ceiling.

    DOI: 10.1007/s40722-025-00385-x

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  2. Anomaly Detection Using Data-Driven Sparse Sensors: Combination of Modal Representation and Sensor Optimization for Sensing of Targeted Variable

    Saito, Y; Inoba, R; Sasaki, Y; Nagata, T; Yamada, K; Nonomura, T

    IEEE SENSORS LETTERS   Vol. 9 ( 8 )   2025.8

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    Publisher:IEEE Sensors Letters  

    We propose an anomaly detection method based on modal representation and a noise-robust sparse sensor position optimization method. We focus on the detection of anomalies in global sea surface temperature field observations indicative of El Niño and La Niña phenomena. For evaluation, we compared four methods, namely, the random linear least squares estimation method, the determinant-based greedy linear least squares method, the DG with noise covariance generalized linear least squares (DG/NC-GLS) estimation, and the Bayesian DG Bayesian estimation (BDG-BE) method of which the extension is proposed in this study. The results demonstrate that the DG/NC-GLS and BDG-BE methods outperform the other methods in anomaly detection. In fact, the DG/NC-GLS and BDG-BE methods achieve high accuracy and precision of over 81% with only 20 sensors (44 219 sensor candidates) for anomaly detection in global sea surface temperature field observations.

    DOI: 10.1109/LSENS.2025.3591066

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  3. Real-time feedback control of flow velocity field using sparse processing particle image velocimetry and plasma actuators Open Access

    Nonomura, T; Abe, C; Naramura, R; Sasaki, Y

    EXPERIMENTS IN FLUIDS   Vol. 66 ( 7 )   2025.7

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    Publisher:Experiments in Fluids  

    Visual feedback control of a flow field by a controller that operates plasma actuators with sparse processing particle image velocimetry as an observer was implemented in a wind tunnel test. The control objective was the suppression of a Kàrmàn vortex around a circular cylinder. Sum-of-absolute-values control based on an L1 optimization problem was implemented to enable real-time processing. Real-time visual feedback control at 2000 Hz was achieved with the proposed system owing to the use of sparse processing particle image velocimetry, which evaluates only a limited number of interrogation windows, and a sophisticated solver for the L1 optimization problem. The techniques adopted in the present study can accelerate the feedback control rate by a factor of 10 to 100. It was confirmed that the proposed system suppresses the Kàrmàn vortex to a certain extent. The results show that the control law using forecasts further ahead performs better.

    DOI: 10.1007/s00348-025-04039-4

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  4. Fast Data-Driven Greedy Sensor Selection for Ridge Regression Reviewed Open Access

    Yasuo Sasaki, Keigo Yamada, Takayuki Nagata, Yuji Saito, Taku Nonomura

    IEEE Sensors Journal   Vol. 25 ( 6 ) page: 10030 - 10045   2025.3

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/JSEN.2025.3537702

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  5. Experimental Analysis of Flow Separation Control by a Dielectric Barrier Discharge Plasma Actuator in Burst-in-Burst Actuation Mode Open Access

    Viguera, R; Sasaki, Y; Nonomura, T

    ACTUATORS   Vol. 13 ( 11 )   2024.11

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    Publisher:Actuators  

    This study investigated the effectiveness of a dielectric barrier discharge (DBD) plasma actuator operating in burst-in-burst (BIB) mode for flow separation control on a NACA 0015 airfoil. Time-resolved particle image velocimetry measurements were conducted at a Reynolds number of 66,000 and 13° angle of attack. Various BIB signal configurations were tested, with actuation periods of 70 ms and 150 ms, non-actuation periods ranging from 5 ms to 50 ms, and burst frequencies of 300 Hz and 600 Hz. Proper orthogonal decomposition was applied to analyze the flow field dynamics. The results showed that BIB actuation maintained flow attachment with reduced power consumption compared with continuous burst actuation. However, the effectiveness was highly sensitive to the BIB parameters, with some configurations failing to achieve consistent reattachment and becoming unstable. This study reveals complex interactions between actuation vortices and separation processes, highlighting both the potential and challenges of intermittent plasma actuation for efficient flow control.

    DOI: 10.3390/act13110435

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  6. Assessment of Sensor Optimization Methods Toward State Estimation in a High-Dimensional System Using Kalman Filter Open Access

    Takayuki Nagata, Yasuo Sasaki, Keigo Yamada, Masahito Watanabe, Daisuke Tsubakino, Taku Nonomura

    IEEE Sensors Journal   Vol. 24 ( 11 ) page: 18012 - 18023   2024.6

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/JSEN.2024.3388849

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  7. Design of reduced-order controllers for fluid flows using full-order controllers and Gaussian process regression Reviewed Open Access

    Yasuo Sasaki, Daisuke Tsubakino

    IFAC Journal of Systems and Control   Vol. 28   page: 100261 - 100261   2024.6

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.ifacsc.2024.100261

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  8. Efficient Sensor Node Selection for Observability Gramian Optimization

    Yamada, K; Sasaki, Y; Nagata, T; Nakai, K; Tsubakino, D; Nonomura, T

    SENSORS   Vol. 23 ( 13 )   2023.7

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    Language:English   Publisher:Sensors  

    Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-invariant, and discrete-time dynamical system are examined under the assumption of independent and identically distributed measurement noise. This study offers two novel selection algorithms, namely an approximate convex relaxation method with the Newton method and a gradient greedy method, and confirms the performance of the selection methods, including a convex relaxation method with semidefinite programming (SDP) and a pure greedy optimization method proposed in the previous studies. The matrix determinant of the observability Gramian was employed for the evaluations of the sensor subsets, while its gradient and Hessian were derived for the proposed methods. In the demonstration using numerical and real-world examples, the proposed approximate greedy method showed superiority in the run time when the sensor numbers were roughly the same as the dimensions of the latent system. The relaxation method with SDP is confirmed to be the most reasonable approach for a system with randomly generated matrices of higher dimensions. However, the degradation of the optimization results was also confirmed in the case of real-world datasets, while the pure greedy selection obtained the most stable optimization results.

    DOI: 10.3390/s23135961

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  9. Determinant-Based Fast Greedy Sensor Selection Algorithm Open Access

    Saito, Y; Nonomura, T; Yamada, K; Nakai, K; Nagata, T; Asai, K; Sasaki, Y; Tsubakino, D

    IEEE ACCESS   Vol. 9   page: 68535 - 68551   2021

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    Publisher:IEEE Access  

    In this paper, the sparse sensor placement problem for least-squares estimation is considered, and the previous novel approach of the sparse sensor selection algorithm is extended. The maximization of the determinant of the matrix which appears in pseudo-inverse matrix operations is employed as an objective function of the problem in the present extended approach. The procedure for the maximization of the determinant of the corresponding matrix is proved to be mathematically the same as that of the previously proposed QR method when the number of sensors is less than that of state variables (undersampling). On the other hand, the authors have developed a new algorithm for when the number of sensors is greater than that of state variables (oversampling). Then, a unified formulation of the two algorithms is derived, and the lower bound of the objective function given by this algorithm is shown using the monotone submodularity of the objective function. The effectiveness of the proposed algorithm on the problem using real datasets is demonstrated by comparing with the results of other algorithms. The numerical results show that the proposed algorithm improves the estimation error by approximately 10% compared with the conventional methods in the oversampling case, where the estimation error is defined as the ratio of the difference between the reconstructed data and the full observation data to the full observation. For the NOAA-SST sensor problem, which has more than ten thousand sensor candidate points, the proposed algorithm selects the sensor positions in few seconds, which required several hours with the other algorithms in the oversampling case on a 3.40 GHz computer.

    DOI: 10.1109/ACCESS.2021.3076186

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  10. Data-Driven Vector-Measurement-Sensor Selection Based on Greedy Algorithm Open Access

    Saito, Y; Nonomura, T; Nankai, K; Yamada, K; Asai, K; Sasaki, Y; Tsubakino, D

    IEEE SENSORS LETTERS   Vol. 4 ( 7 )   2020.7

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    Publisher:IEEE Sensors Letters  

    A vector-measurement-sensor problem for the least squares estimation is considered, by extending a previous novel approach in this letter. An extension of the vector-measurement-sensor selection of the greedy algorithm is proposed and is applied to particle-image-velocimetry data to reconstruct the full state based on the information given by sparse vector-measurement sensors.

    DOI: 10.1109/LSENS.2020.2999186

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  11. Designs of Feedback Controllers for Fluid Flows Based on Model Predictive Control and Regression Analysis Reviewed Open Access

    Yasuo Sasaki, Daisuke Tsubakino

    MDPI Energies   Vol. 13 ( 6 )   2020.3

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3390/en13061325

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MISC 1

  1. Feedback Controller Design for Fluid Fields based on Model Predictive Control and Regression Analysis

    SASAKI Yasuo, TSUBAKINO Daisuke

    Journal of The Society of Instrument and Control Engineers   Vol. 59 ( 8 ) page: 546 - 551   2020.8

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    Authorship:Lead author, Last author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:The Society of Instrument and Control Engineers  

    DOI: 10.11499/sicejl.59.546

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Presentations 15

  1. Ginzburg-Landauモデルに対する有限ホライズン最適制御則の次元削減とニューラルネットワークを利用した近似

    第12回計測自動制御学会制御部門マルチシンポジウム  2025.3.4 

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    Event date: 2025.3

    Language:Japanese   Presentation type:Oral presentation (general)  

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  2. 線形化Ginzburg-Landauモデルに対する線形二次Gaussian制御器の低次元化

    佐々木康雄

    日本流体力学会 年会2024  2024.9.27 

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    Event date: 2024.9

    Language:Japanese   Presentation type:Oral presentation (general)  

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  3. Physics-Informed Neural Networksを利用したある一次元偏微分方程式の最適制御

    佐々木康雄

    第67回 理論応用力学講演会  2024.9.4 

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    Event date: 2024.9

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  4. 大規模な線形時変システムの可到達集合最大化のためのアクチュエータ選択―Lorenz 96モデルへの適用―

    佐々木康雄, 永田貴之, 渡辺昌仁, 野々村拓, 伊藤純至, 椿野大輔

    計測自動制御学会 第11回 制御部門マルチシンポジウム  2024.3.18 

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    Event date: 2024.3

    Language:Japanese   Presentation type:Oral presentation (general)  

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  5. 大規模な線形時変システムに対する特異値分解を利用した最適アクチュエータ選択―Lorenz 96モデルへの適用―

    佐々木康雄, 山田圭吾, 永田貴之, 渡辺昌仁, 野々村拓, 伊藤純至, 椿野大輔

    第66回自動制御連合講演会  2023.10.8 

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    Event date: 2023.10

    Language:Japanese   Presentation type:Oral presentation (general)  

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  6. Fast Linear-regression-based Sensor Selection and its Applications

    Yasuo Sasaki, Yuji Saito, Takayuki Nagata, Keigo Yamada, Taku Nonomura

    International Council for Industrial and Applied Mathematics  2023.8.23 

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    Event date: 2023.8

    Language:English   Presentation type:Oral presentation (general)  

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  7. Heuristic Actuator Selection With the use of Data of Nonlinear Optimal Control for Fluid Flows

    Yasuo Sasaki, Taku Nonomura

    The 22nd World Congress of the International Federation of Automatic Control  2023.7.13 

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    Event date: 2023.7

    Language:English   Presentation type:Oral presentation (general)  

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  8. Data-Driven Controller Design and Sensor Selection for Flow Around a Circular Cylinder

    Yasuo Sasaki, Taku Nonomura

    75th Annual Meeting of the APS Division of Fluid Dynamics  2022.11.20 

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    Event date: 2022.11

    Language:English   Presentation type:Oral presentation (general)  

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  9. 円柱周り流れに対する動的モード分解と可制御性グラミアンを利用したアクチュエータ選択

    佐々木康雄, 山田圭吾, 野々村拓

    第65回自動制御連合講演会  2022.11.13 

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    Event date: 2022.11

    Language:Japanese   Presentation type:Oral presentation (general)  

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  10. 円柱周り流れに対するモデル予測制御のデータを用いた制御則設計とセンサ選択最適化

    佐々木康雄, 椿野大輔, 野々村拓

    日本流体力学会 年会2022  2022.9.27 

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    Event date: 2022.9

    Language:Japanese   Presentation type:Oral presentation (general)  

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  11. Output-Feedback Controller Design for a Detailed Model of Flow Around a Cylinder

    Yasuo Sasaki, Daisuke Tsubakino

    AIAA SCITECH 2022 Forum  2022.1.4 

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    Event date: 2022.1

    Language:English   Presentation type:Oral presentation (general)  

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  12. Design of Reduced-Order Controllers for Flow Fields Using Full-Order Controllers

    Yasuo Sasaki, Daisuke Tsubakino

    2021.11.13 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

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  13. Approximation of the Ensemble Kalman Filter for Flow around a Cylinder Using Machine Learning Techniques

    Yasuo Sasaki, Daisuke Tsubakino

    2020.11.22 

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    Event date: 2020.11

    Presentation type:Oral presentation (general)  

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  14. Design of Observers for the Flow Around a Cylinder Using Machine Learning Techniques

    Yasuo Sasaki, Daisuke Tsubakino

    SICE Annual Conference 2020  2020.9.26 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

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  15. System Identification of Dynamic Control Laws for Fluid Flows around a Circular Cylinder

    Yasuo Sasaki, Daisuke Tsubakino

    2020.3.5 

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    Event date: 2020.3

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KAKENHI (Grants-in-Aid for Scientific Research) 2

  1. Control System Design Using Full-Order Control Law and Data Analysis for Fluid Fields

    Grant number:23K13348  2023.4 - 2027.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Early-Career Scientists

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    Authorship:Principal investigator 

    Grant amount:\4550000 ( Direct Cost: \3500000 、 Indirect Cost:\1050000 )

  2. Design of Control Laws for Flow Fields by Using Machine Learning and Control Theory

    Grant number:21J14180  2021.4 - 2023.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for JSPS Fellows

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    Authorship:Principal investigator 

    Grant amount:\1500000 ( Direct Cost: \1500000 )

 

Teaching Experience (Off-campus) 1

  1. グリーン・データ科学特別講義

    2023 Tohoku University)

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