The valve opening control of the motor-operated valve using virtual internal model tuning and vata-driven prediction

This paper deals with applications of data-driven control, which is a controller tuning method that directly utilizes the data, for mechanical systems. Particularly, we focus on the valve opening control of the motor-operated valve as one of the representative mechanical control units which are used...

Full description

Bibliographic Details
Main Authors: Taichi IKEZAKI, Miku IKESAWA, Osamu KANEKO, Kohei FUTAMATAGAWA, Kei HIGUCHI, Hiroaki NARITA, Hiroshi YADOIWA
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2023-02-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/transjsme/89/919/89_22-00237/_pdf/-char/en
Description
Summary:This paper deals with applications of data-driven control, which is a controller tuning method that directly utilizes the data, for mechanical systems. Particularly, we focus on the valve opening control of the motor-operated valve as one of the representative mechanical control units which are used in much industrial equipment and are needed to be precisely controlled. If we have a mathematical model of such a system, a model-based controller design is the most rational approach. Otherwise, data-driven controller tuning is also expected to be a rational approach. However, there exists a nonlinear characteristic, such as the limit of a speed implemented in the nonlinear compensator. Since conventional data-driven controller design can not be used because data-driven control is generally derived for only linear time-invariant systems, we have to modify the method of driven controller tuning method so as to be applicable for such systems. This paper proposes a controller tuning method for the valve-opening control system implemented as a cascade control system with a limit of the speed. Here, we apply Virtual Internal Model Tuning, which is abbreviated as VIMT, to tune the inner linear controller. Then, we also apply data-driven prediction to compute the outer loop controller including the limit of the speed. Finally, we verified the usefulness of the proposed method using experimental verification.
ISSN:2187-9761