Curriculum Vitaes

Natsuki Kawaguchi

  (川口 夏樹)

Profile Information

Affiliation
University of Hyogo
Degree
博士(工学)(Mar, 2018, 兵庫県立大学大学院)

Researcher number
90824392
J-GLOBAL ID
201801018128759047
researchmap Member ID
B000308931

Research History

 2

Papers

 96
  • Natsuki Kawaguchi, Sae Fujita, Takao Sato
    Journal of Robotics and Mechatronics, 38(1), 2026  Peer-reviewedLead author
  • Wataru Hashimoto, Naoki Hayashi, Naoyuki Hara, Natsuki Kawaguchi, Takao Sato, Shigemasa Takai
    International Journal of Control, 1-13, Jul 29, 2025  
  • Kota Jinai, Yusuke Tsunoda, Natsuki Kawaguchi, Orlando Arrieta, Takao Sato
    Journal of Robotics and Mechatronics, 37(3) 688-699, Jun 20, 2025  Peer-reviewed
    This study proposes a data-driven optimal robust design methodology for a fractional-order proportional-integral-derivative (FOPID) controller. This methodology concurrently determines the parameters of the FOPID controller and reference model under a stability-margin constraint by utilizing only one-shot input-output data. The stability margin, which is quantitatively defined as the maximum value of the sensitivity function, is specified by the designer. This approach ensures a balanced design based on the trade-off between robust stability and servo or regulator performance at a given robust-stability level. Numerical examples substantiate the superiority of the FOPID controller over the conventional integer-order proportional-integral-derivative controller.
  • Ryota Ohnishi, Ippei Tanaka, Natsuki Kawaguchi, Yasunori Harada
    Nanomanufacturing and Metrology, 8(1), May 13, 2025  Peer-reviewed
  • Kenta Nagao, Natsuki Kawaguchi, Takao Sato
    Electronics and Communications in Japan, 108(2), Apr 29, 2025  
    ABSTRACT In control systems using network communication or digital sensors, the quantization of input and output signals can significantly impact control performance. Therefore, it is essential to incorporate signal quantification into the control system design to prevent performance degradation. This study proposes a controller design method for systems in which both inputs and outputs are quantized. The proposed method derives a controller that minimizes the upper bound of the error between a plant output and a reference model output. In contrast to previous studies, our proposed method avoids solving matrix inequalities numerically and provides an analytical design approach.

Misc.

 7

Presentations

 68

Research Projects

 5

Academic Activities

 6