Paper
24 November 1999 GA-based PID control of the plate width in hot-plate mills
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Abstract
In hot plate mills the slabs from incoming reheat furnace are reduced to the desired width and thickness, being rolled out with considerable accuracy. The process of changing the plate width is controlled by a pair of edge rolls, which is called edger. The objectives of this edging process are to meet tight width tolerances of plates and to reduce the yield loss caused by trimming when irregular width is formed at the plate edge. There are several factors that result in complexity and uncertainty in width control. These include inaccurate edger set-up model, degradation of various mill equipment, variation of operation conditions, environments and variation of the dimension of incoming cast slabs. In this paper, a genetic algorithm-based PID control is proposed to ensure the control of the desired width at the exit of the mill. The approach adopted here is essentially optimization of the PID controller gains in order to minimize the error between the desired and actual slab width. Since the design parameters associated with genetic algorithm affect convergence performance, the effects of these parameters are investigated in detail. In addition, the control performance is also evaluated for various process parameters such as initial width of the incoming slab and temperature of the slab. Based on the result obtained from a series of simulations, the proposed control method is found to yield satisfactory performance for various process conditions.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Byungman Kim, Dae Yup Lee, and Hyungsuck Cho "GA-based PID control of the plate width in hot-plate mills", Proc. SPIE 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics, (24 November 1999); https://doi.org/10.1117/12.371176
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Cited by 1 scholarly publication.
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KEYWORDS
Control systems

Process control

Servomechanisms

Process modeling

Genetics

Error analysis

Promethium

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