Model-Based Flow Rate Control with Online Model Parameters Identification in Automatic Pouring Machine

被引:2
|
作者
Kabasawa, Nobutoshi [1 ]
Noda, Yoshiyuki [2 ]
机构
[1] Univ Yamanashi, Integrated Grad Sch Med Engn & Agr Sci, Course Mech Engn, 4-3-11, Kofu, Yamanashi 4008511, Japan
[2] Univ Yamanashi, Grad Fac Interdisciplinary Res, Dept Mech Engn, 4-3-11, Kofu, Yamanashi 4008511, Japan
关键词
flow rate control; automatic pouring machine; parameters identification; model-based control; OPTIMIZATION;
D O I
10.3390/robotics10010039
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this study, we proposed an advanced control system for tilting-ladle-type automatic pouring machines in the casting industry. Automatic pouring machines have been introduced recently to improve the working environment of the pouring process. In the conventional study on pouring control, it has been confirmed that the pouring flow rate control contributes to improving the accuracy of the entire automatic pouring machine, such as the outflow liquid's falling position from the ladle, the liquid's weight filled in the mold, and the sprue cup's liquid level. However, the conventional control system has problems: it is not easy to precisely pour the liquid in the ladle with a large tilting angle, and it takes time to adjust the control parameters. Therefore, we proposed the feedforward pouring flow rate control system, constructed by the pouring process' inverse model with the online model parameters identification. In this approach, we derived the pouring process' mathematical model, representing precisely the pouring process with the ladle's large tilting angle. The model parameters in the pouring process' inverse model in the controller are updated online via the model parameters identification. To verify the proposed pouring control system's efficacy, we experimented using the tilting-ladle-type automatic pouring machine. In the experimental results, the mean absolute error between the outflow liquid's weight and the reference weight was improved from 0.1346 at the first pouring to 0.0498 at the fifth pouring. Moreover, the model parameters were identified within 4 s. Therefore, it enables updating the controller's parameters within each pouring motion interval by the proposed approach.
引用
收藏
页数:17
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