Murakami, Toshiyuki

写真a

Affiliation

Faculty of Science and Technology, Department of System Design Engineering （Yagami）

Position

Professor

External Links
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  • Prof. Toshiyuki MURAKAMI received the B. E., M. E., and Ph. D. degrees in electrical engineering from Keio University, Yokohama, Japan, in 1988, 1990, and 1993, respectively. In 1993, he joined the Department of Electrical Engineering, Keio University, where he is currently a Professor in the Department of System Design Engineering. From 1999 to 2000, he was a Visiting Researcher with The Institute for Power Electronics and Electrical Drives, Aachen University of Technology, Aachen, Germany. His research interests are robotics, intelligent vehicles, mobile robots, and motion control.

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Profile Summary 【 Display / hide 】

  • '''''''This laboratory focuses on robot control/instrumentation and sensor applicationa to achieve a flexible human assist (FHA) system. Areas investigated include sensor application, intelligent wheelchair control, vibration control, mobile manipulator control, and intelligent manufacturing systems; areas yielding many conference papers and articles.'''''''

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Other Affiliation 【 Display / hide 】

  • Dean, Faculty of Science and Technology

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Career 【 Display / hide 】

  • 1993.04
    -
    1996.03

    慶應義塾大学理工学部電気工学科 ,助手

  • 1996.04
    -
    Present

    慶應義塾大学理工学部システムデザイン工学科 ,専任講師

  • 1996.04
    -
    Present

    慶應義塾大学理工学部電気工学科 ,専任講師

  • 1997.04
    -
    1999.03

    慶應義塾大学理工学部情報処理常置委員会　 ,委員

  • 1998.04
    -
    1999.03

    慶應義塾大学日吉２学年 ,担任

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Academic Background 【 Display / hide 】

  • 1988.03

    Keio University, Faculty of Science and Engineering, 電気工学科

    University, Graduated

  • 1990.03

    Keio University, Graduate School, Division of Science and Engineeri, 電気工学専攻

    Graduate School, Completed, Master's course

  • 1993.03

    Keio University, Graduate School, Division of Science and Engineeri, 電気工学専攻

    Graduate School, Completed, Doctoral course

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Academic Degrees 【 Display / hide 】

  • 工学　, Keio University, 1993.03

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Research Areas 【 Display / hide 】

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Power engineering (Electric Power Engineering/Electric Equipment Engineering)

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Research Keywords 【 Display / hide 】

  • Robotics, Motion Control

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Books 【 Display / hide 】

  • 「電磁気工学」

    村上俊之，内山太郎，大西公平, 培風館, 2002.05

    　View Summary

    力を中心とした電磁気工学の基礎事項および電磁気工学に基づいた実機応用について概説した教科書である．

  • 数理工学基礎シリーズ「コンピュータの数理」

    矢向高弘、村上俊之、大西公平, 朝倉書店, 2000.10

    　View Summary

    コンピュータのハードウェアの基礎から、2進数による数値計算法、C言語によるプログラミング、計算誤差にまで言及した工学者向けの教科書である。

  • Recent Advances in Motion Control (邦訳 : モーション・コントロールの最新技術)

    G.S.Buja, H.Fujita and K.Ohnishi, 日刊工業新聞社, 1990.12

    Scope: 3〜12, 131〜138

    　View Summary

    G.S.Buja, H.Fujita and K.Ohnishi のうちChapter 1-1 'Advanced Control Technique inMotion System', pp3〜12, 及びChapter 6-2 'An Approach to Artificial MuscleMotion by Network of Actuators', pp131〜138, 本著書では，多自由度モーションシステムにおけるロバスト制御技術の最新技術について述べている．同時に，モーションシステムの自

  • Integrated Micro-Motion Systems　-Micromachining, Control and Applications- (邦訳 : マイクロモーション統合システム)

    Edited by F.Harashima, Elsevier Science Publishers B.V., 1990.12

    Scope: 185〜198

    　View Summary

    Edited by F.Harashima のうちNetwork Motion Control in Micromechatronics, pp185〜198,本著書では，近年注目されているマイクロアクチュエータを想定した多自由度システムの構成法ならびにその力制御手法について述べている．本手法の特長は，非線形フィードバックにより，力の動作信号が孤立波としてアクチュエータ間を伝搬する機構となっている点にある．提案する手法の有効性は数値シミュレーションにより確認されている．

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Papers 【 Display / hide 】

  • Identification of unknown object properties based on tactile motion sequence using 2-finger gripper robot

    Thompson J., Kasun Prasanga D., Murakami T.

    Precision Engineering （Precision Engineering)  74   347 - 357 2022.03

    ISSN  01416359

    　View Summary

    The purpose of service robots is to work and handle a wide range of objects in a human environment. Therefore, they must have the ability to grasp unknown objects with the appropriate force, by dynamically identifying their stiffness, mass, and surface-interaction properties. To ensure the successful grasping of unknown objects, it is significant to estimate the object response properties. In this paper, the cognitive functions to efficiently perform such operations with only tactile motion data and supervised learning using limited data, have been demonstrated. The study uses pinch-grasping performed by a 2-fingered robot experimental setup with a pre-designed motion sequence, over 7 different objects having a wide range of properties to capture the motion data. The proposed approach avails pre-processed motion data to train neural networks for accurately predicting object response properties for 3 unseen test objects. We have done a comparative study among three neural network architectures CNN, LSTM, and CNN-LSTM and we found that novel CNN-LSTM outperforms the other two models in terms of accuracy. The CNN-LSTM regression model achieves 0.98 and 0.97 of R2 value for the prediction of stiffness and mass, respectively and the CNN classification model achieves 94% of accuracy for the surface interaction classification.

  • An Approach of Load-Side Disturbance Rejection Control for Series Elastic Actuators

    Hiraoka Atsushi, Murakami Toshiyuki

    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    18 - 23 2022

    ISSN  1943-6572

  • Classification of Older and Fall-Experienced Subjects by Postural Sway Data using Mass Spring Damper Model.

    Yuta Tawaki, Takuichi Nishimura, Toshiyuki Murakami

    IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society （IEEE Transactions on Neural Systems and Rehabilitation Engineering)  30   40 - 49 2022

    ISSN  15344320

    　View Summary

    The quiet standing test is used to detect diseases of the postural control system. The descriptive statistics of the center of pressure (COP) of older people during the test tend to be larger than those of healthy young people, but they cannot indicate structural problems in postural control. COP trajectories can be mathematically modeled with structural parameters such as viscosity, stiffness, and stochastic terms; however, the classification accuracy of older and fall-experienced people using such parameters has not been sufficiently verified. In this study, six structural parameters of a mass-spring-damper (MSD) model were estimated using two datasets, in which a total of 212 subjects performed quiet standing tests under four conditions. The estimated parameters were used for classification with a random forest algorithm to examine the differences in classification accuracy compared to seven conventional descriptive statistics methods. For the classification of older subjects, the classification accuracy of the MSD parameter method was the highest in foam condition, with positive likelihood ratios approximately 8.0. For the classification of fall-experienced subjects, the positive likelihood ratio of the MSD parameter method was 5.0, which is better than conventional descriptive statistics. Various MSD parameters revealed that aging and changing the floor surface and visual conditions cause oscillations in the COP behavior. While the MSD parameters were confirmed to help classify older subjects more accurately than the conventional descriptive statistics, there was room for further improvement in the classification accuracy of fall-experienced subjects.

  • Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control based Position-Sensorless Control of IPMSM

    Shimamoto K., Murakami T.

    IEEE Access （IEEE Access)   2022

    　View Summary

    This paper presents a control method with an estimation method of cross-coupling factors of Interior Permanent Magnet Synchronous Motors (IPMSM) inductance for position-sensorless servo drive systems. The cross-coupling factors are from dq-axis mutual inductance. Conventionally, the cross-coupling factors have been ignored in the IPMSM model and deteriorate control performance. That has caused decreasing robustness and velocity vibration in the low-speed range. Since the cross-coupling factors vary with the rotor position and the current, it is hard to measure them. Therefore, the proposed method utilizes a high-frequency voltage injection method to estimate the cross-coupling factors online. In addition, the proposed current control method utilizes a sliding mode control and voltage disturbance observer based on the voltage equation, including the dq-axis mutual inductance model. The estimated cross-coupling factors are reflected in the proposed current controller instantaneously. Experimental results show that the proposed method considering cross-coupling factors increases the robustness to the disturbance force and reduces the velocity vibration.

  • Performance Evaluation of Force Control and Reaction Force Estimation in Force Sensorless Hybrid Control for Workspace Based Controller

    Shimamoto Keita, Murakami Toshiyuki

    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    231 - 236 2022

    ISSN  1943-6572

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Reviews, Commentaries, etc. 【 Display / hide 】

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Presentations 【 Display / hide 】

  • An Approach to Power Assist Hand Exoskeleton for Patients with Paralysis

    H. Uchida and T. Murakami

    IEEE 15th International Workshop on Advanced Motion Control (Nagaoka University of Technology, Japan) , 

    2018.03
    , 

    Oral presentation (general)

  • Automated Deceleration System Considering Driving Resistance Based on Pedestrian’s Forecast Position

    Y. Nakamura, T. Nozaki and T. Murakami

    The IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization (SAMCON2018) (Nagaoka University of Technology, Japan) , 

    2018.03
    , 

    Oral presentation (general)

  • Comprehensive Evaluation of Human Activity Classification based on Inertia Measurement Unit with Air Pressure Sensor

    T. Ishikawa, H. Hayami and T. Murakami

    2017 IEEE 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP2017) (Nagaoka University of Technology, Japan) , 

    2017.11
    , 

    Oral presentation (general)

  • Position and Torque Sensorless Motion Transmission for Haptic Teleoperation Using Two Types of Voltage Compensation

    S. Akutsu, T. Nozaki and T. Murakami

    2017 IEEE 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP2017) (Nagaoka University of Technology, Japan) , 

    2017.11
    , 

    Oral presentation (general)

  • A Comparison Study of Velocity and Torque Based Control of Two-Wheel Mobile Robot for Human Operation

    S. Amagai, M. Kamatani and T. Murakami

    2017 IEEE 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP2017) (Nagaoka University of Technology, Japan) , 

    2017.11
    , 

    Oral presentation (general)

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • A Study on Human Motion Model and Force Control Based Life Support for ADL

    2015.04
    -
    2018.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (A) , Principal investigator

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Awards 【 Display / hide 】

  • 電気学会産業応用特別賞貢献賞

    2022.08

  • Best Paper Award

    2021.03, The 9th IIAE International Conference on Industrial Application Engineering 2021

    Type of Award： Award from international society, conference, symposium, etc.

  • Best Poster Award

    2021.03, The 9th IIAE International Conference on Industrial Application Engineering 2021

    Type of Award： Award from international society, conference, symposium, etc.

  • 電気学会　フェロー

    2016.04

  • IEEJ Industry Applications Society Distinguished Transaction Paper Award

    Misako Sasayama and Toshiyuki Murakami, 2015.09, （社）電気学会

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Courses Taught 【 Display / hide 】

  • SEMINAR IN SYSTEM DESIGN ENGINEERING

    2023

  • INTELLIGENT MACHINE SYSTEM

    2023

  • INDEPENDENT STUDY ON INTEGRATED DESIGN ENGINEERING

    2023

  • GRADUATE RESEARCH ON INTEGRATED DESIGN ENGINEERING 2

    2023

  • GRADUATE RESEARCH ON INTEGRATED DESIGN ENGINEERING 1

    2023

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Memberships in Academic Societies 【 Display / hide 】

  • 電気学会東京支部学生員委員会, 

    2005.05
    -
    2006.05

  • 電気学会 平成１７年度産業応用部門大会論文委員会, 

    2004.12
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    2005.11

  • 電気学会 センサの知能化によるシステムの高度化協同研究委員会, 

    2004.11
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    2006.10

  • 電気学会 産業応用部門国際化ＷＧ, 

    2004.09
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    2005.09

  • 電気学会 東京支部役員会, 

    2004.05
    -
    2006.05

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Committee Experiences 【 Display / hide 】

  • 2021.08
    -
    2023.07

    委員, 電気学会 多技術融合による高度センサ応用に関する調査専門に員会

  • 2021.05
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    2022.03

    顧問, SAMCON2022実行委員会

  • 2020.09
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    2022.05

    委員, 電気学会表彰委員会

  • 2020.06
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    Present

    1号委員, 電気学会 電気システムセキュリティ特別技術委員会

  • 2020.06
    -
    2022.06

    部門長・部門担当理事（産業応用部門）, 電気学会

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