Ryota Uematsu and Shiro Masuda, Data-driven Generalized Minimum Variance Regulatory Control Using Routine Operation Data, Asian Journal of Control, early view, https://doi.org/10.1002/asjc.2776
Shotaro Shiroi, Shiro Masuda, Pre-Filter Design for Iterative Controller Parameter Tuning Using Data-Driven Minimum Variance Regulatory Controllers, IEEJ Transactions on Electrical and Electronic Engineering, Vol. 16, No. 10, pp.1429-1434, 2021
Ryota Uematsu and Shiro Masuda, Closed-loop Identification and Dead Time Estimation Based on Generalized Minimum Variance Evaluation, 2021 European Control Conference (ECC) , June 29 - July 2, 2021, Rotterdam, NL (Online)
Ryota Uematsu and Shiro Masuda, Closed-loop Identification and Periodic Disturbance Estimation Based on Generalized Minimum Variance Evaluation, 2021 25th International Conference on System Theory, Control and Computing (ICSTCC), 20-23 Oct. 2021, Iasi, Romania (Online)
Yui Takano, Shiro Masuda, Iterative Feedback Tuning for Regulatory Control Systems with Measurable Disturbances, 3rd IFAC Conference on Modelling, Identification and Control of Nonlinear Systems MICNON 2021, Tokyo, Japan, 15-17 September 2021 (Online)
Taihei Mikami, Shiro Masuda, Yoshihiro Matsui, Data-driven Closed-loop Update Tuning Taking Account of Stability Margin, 2021 International Conference on Advanced Mechatronic Systems (ICAMechS), 9-12 Dec. 2021 (Online)
Yuna Takahashi and Shiro Masuda, Data-driven Successive Economic Performance Improvement for Model Predictive Control Taking Account of Variance Evaluation of Manipulated Variables, SICE Annual Conference 2021, Sep. 8-10, 2021, at Yotsuya Campus, Sophia University, Tokyo (Online)
Yoshihiro Matsui, Hideki Ayano, Shiro Masuda, Kazushi Nakano, Impulse Response Estimation of a Resonant Mechanical System Using Closed-Loop Data, SICE Annual Conference 2021, Sep. 8-10, 2021, at Yotsuya Campus, Sophia University, Tokyo (Online)