Data‐Driven Controller Tuning for Unmeasurable Outputs to Achieve Desired Tracking Properties. Issue 10 (7th August 2021) - Suzuki, Motoya; Kaneko, Osamu
Abstract : Conventional parameter‐tuning methods, such as virtual reference feedback tuning and fictitious reference iterative tuning (FRIT), are not applicable to plants where the variables to be controlled cannot be measured. In this work, we propose a new method of controller parameter tuning for this class of systems. In the proposed method, the controller can be tuned using one‐shot experimental observation and manipulation data. The proposed method can help tune the controller parameters without the plant model by using a manipulated variable and an observed variable. The validity of the proposed methods was also verified by a motor speed‐control experiment. The experimental results show that the proposed method can help realize good control parameters without observing the controlled variable. Compared to FRIT, the proposed method has the following advantages: the closed‐loop response is very close to the desired response even if the output signals cannot be observed. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.