Process Systems Engineering Laboratory
Tokyo University of Agriculture and Technology (TUAT)

Smart Chemical Plant

We are investigating methods to realize smart chemical plants and a smart sustainable society. Process control and monitoring are most major studies in our laboratory. Both chemical engineering and artificial intelligence are fully utilized to solve difficult problems.


  • Process Systems Engineering
  • Chemical Engineering
  • Artificial Intelligence
  • Process Control
  • Process Operation

Recent News

SCEJ 85th Annual Meeting

Yamashita, Otakara and Taguchi, each, presented their papers at the SCEJ 85th Annual Meeting, although the realtime event was cancelled because of COVID-19.

SCEJ 22nd Student Meeting

Ishihara, Ohashi, Taosamaru and Matsumura, each, presented their research works on SCEJ 22nd Student Meeting, although the realtime event was cancelled because of COVID-19.

62nd Automatic Control Conference

Taguchi, Xia and Nakano, each, presented papers on 62nd Automatic Control Conference (Sapporo).

SCEJ 18th Process Design Student Contest

Ishihara et al attended the SCEJ 18th Process Design Student Contes at Yokohama and won several awards such as Design policy award and so on.

FOPAM 2019

Prof. Yamashita attended FOPAM (Raleigh, NC).

Recent Talks

Japan-Thailand Symposium on Smart Industrial Safety 2020

On February 19 (Wed.), 2020, the Ministry of Economy, Trade and Industry (METI) hold Japan-Thailand Symposium on Smart Industrial Safety. Professor Yamashita gave a keynote talk at the symposium.


From November 20th to 22nd, 2019, INCHEM TOKYO 2019 was held at Makuhari Messe Event Hall, near Tokyo. Professor Yamashita gave a special lecture about digital transformation of chemical plants.

Recent Publications

Quickly discover relevant content by filtering publications.

Process-Identification and Design of Robust PI Controller for a Self-Oscillating Integral Process with Dead Time

This paper proposes a practical method to identify the process dynamics for an integral process with dead-time, under continuous …

A Hybrid Approach for Process Optimization of Distillation Reflux Condition using First Principle Models and Least Squares Regression

Distillation columns are conventionally controlled at fixed reflux ratio to maintain the quality of the overhead product. If the …

Modeling and Optimization of the Hot Compressed Water Extraction of Palm Oil Using Artificial Neural Network

Hot compressed water extraction (HCWE) is a promising green alternative to the screw press in the palm oil processing. In this study, …

Improving Data Reliability for Process Monitoring with Fuzzy Outlier Detection

To implement on-line process monitoring techniques that utilize principal component analysis (PCA) or partial least squares (PLS) …

Practical application of model identification based on ARX models with transfer functions

A novel model identification methodology for ARX models based on transfer functions has been proposed. The identification approach …

Laboratory Members

Lab Members

  • Professor
  • Assistant Professor
  • Graduate Students
    • Tomoyuki Taguchi (D4)
    • Xia Junqing (D4)
    • Shigeki Ootakara (D2)
    • Masaharu Daiguji (D2)
    • Takashi Yamaguchi (D2)
    • Chinatsu Ukawa(M2, D0)
    • Shoutaro Ishihara (M1)
    • Mikihisa Taosamaru (M1)
    • Yasunari Matsumura (M1)
    • Yuuto Ohashi (M1)
  • Undergraduate Students
    • Moe Kato(B4)
    • Natsumi Sato(B4)
    • Yu Suzuki(B4)


Members Only Page


  • 2-24-16 Naka-cho, Koganei, Tokyo 1848588
  • Enter Building 13 and take the elevator to Office 804 on Floor 8