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허윤기(Yone-Gi Hur) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.10
The strip shape for the stainless steel process has made an issue of the strip quality, and hence the shape control method is developed at the Sendzimir rolling mill (ZRM). ZRM is a stainless cold rolling mill and has actuators for the shape control. They are first intermediate rolls and top crown rolls, which are controlled horizontally and vertically, respectively. The shape control of the stainless steel rolling process has difficulty in obtaining the symmetrical shape. The objective of the shape control is to minimize the shape deviation and to maintain stable state, which keeps symmetrical shape pattern in the lateral direction. The method of the shape recognition employs a least squares method and neural network. The shape deviation is the difference between the target shape and actual shape and is controlled by the fuzzy shape control. The fuzzy shape control using operator’s informative knowledge is proposed in this paper. The experiments are carried out online for various stainless materials and sizes. The productivity of the rolling process has increased from 9.0 to 9.4 tons per hour.
허윤기(Yone-Gi Hur),최영규(Young-Kiu Choi) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.6
The plate manufacturing processes are composed of the reheating furnace, finishing mill, cooling process and hot leveling. The finishing rolling mill (FM) as a reversing mill has produced the plate steel through multiple pass rolling. The automatic gauge control (AGC) is employed to maintain the thickness tolerance. The high grade products are forming greater parts of the manufacturing and customers are requiring strict thickness margin. For this reason, the advanced AGC method is required instead of the conventional AGC based on the PI control. To overcome the slow response performance of the conventional AGC and the thickness measurement delay, a fuzzy AGC based on the thickness deviation and its trend is proposed in this paper. An embedded controller with the fuzzy AGC has been developed and implemented at the plate mill in POSCO. The fuzzy AGC has dynamically controlled the roll gap in real time with the programmable logic controller (PLC). On line tests have been performed for the general and TMCP products. As the results, the thickness deviation range (maximum - minimum of the inner plate) is averagely from 0.3 to 0.1 mm over the full length. The fuzzy AGC has improved thickness deviation and completely satisfied customer needs.
허윤기(Yone-Gi Hur) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.10
The hot rolling process ranks the highest position for production in steel making process. The hot strip manufacturing processes consist of the reheating furnace, roughing and finishing mill and coiler. The reheating furnace heats the slab. The roughing and finishing mill produce the hot strip from slab. The hot strip quality mainly depends on finishing mill, which consists of 4-high 7 stands. The looper is installed between stands and is used for controlling the strip tension by the looper angle for better material flow. It is difficult to control the strip tension with the coupled looper system from interaction between the looper angle and strip tension. Too much deviation of strip tension severely affects the poor width quality of the hot strip. It is important to control simultaneously both the looper angle and strip tension with each of their target values. This paper proposes the fuzzy tension control, which is developed to minimize the width deviation of the hot strip by maintaining the proper strip tension between stands and to achieve the stable operation of the coupled looper system. The fuzzy tension control performance is compared with the conventional PID control by experimental results.