Yoichiro Ashida, Ph.D.

Research Leadership

I lead the Ashida Laboratory at the National Institute of Technology (KOSEN), Matsue College. I independently conduct and supervise research in control and systems engineering, including data-driven control, predictive control, PID control, and control-system applications.

I supervise research students in both the Department of Electrical Engineering and Computer Science and the Advanced Course of Electronic and Information Systems.

Research Profiles: Research map | J-GLOBAL

Current Research

Our research focuses on the development and application of advanced control methodologies, with particular interests in:

* Data-driven control and controller tuning

* Predictive Functional Control (PFC)

* PID control and performance improvement

* Feedforward and disturbance-rejection control

* Machine learning and data-driven modeling for control systems

* Experimental implementation of control algorithms

Our research typically combines theoretical development, numerical simulation, and experimental validation.

Lab Members
Department of Electrical Engineering and Computer Science: 4 students
Lab member as a start-up seminor: 4 students
Advanced Electronic and Information Systems: 2 students

Selected Recent Publications

Y. Ashida et al., “Data-Driven Prediction of Nonlinear Closed-Loop Responses Using Reservoir Computing within the FRIT Framework for Controller Design”, Proceedings of the 2025 SICE Festival with Annual Conference, 2025.

S. Takagi and Y. Ashida, “Data-Driven Design of a Feedback-Feedforward Predictive Functional Controller for Setpoint Tracking and Disturbance Rejection“,   Proceedings of the 2025 SICE Festival with Annual Conference, 2025.

Y. Ashida and M. Katayama, “Design of a Model-Free Controller based on Predictive Functional Control”, IEEJ Transactions on Electronics, Information and Systems,  Vol. 144, Issue 1, pp. 15–20, 2024 (in Japanese and translated to English).

Y. Ashida, S. Wakitani, and T. Yamamoto, “Design of an Augmented Output-Based Multiloop Self-Tuning PID Control System“, Industrial & Engineering Chemistry Research Vol. 58, Issue 26, pp. 11474-11484, 2019