• Title/Summary/Keyword: Ceramic drying electric furnace

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Generalized predictive control with exponential weight to control tempera-tures in ceramic drying furnace (세라믹 건조로 온도 제어를 위한 가중계수를 갖는 일반형 예측제어)

  • 임태규;성원준;금영탁;송창섭
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.13 no.6
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    • pp.284-289
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    • 2003
  • The electric furnace, inside which the desired temperature is kept by the generated heat, is known to be a difficult system to control and model exactly because system parameters and response delayed time are varied as the temperature and positions are changed. In this study, the GPCEW (generalized predictive control with exponential weight), which always guarantees the stability of the closed loop system and can be effectively applied to the internally unstable system, was introduced to the ceramic drying electric furnace and was verified by showing its temperature tracking performance experimentally.

Temperature Control of Electric Furnaces using Adaptive Time Optimal Control (적응최적시간제어를 사용한 전기로의 온도제어)

  • Jeon, Bong-Keun;Song, Chang-Seop;Keum, Young-Tag
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.5
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    • pp.120-127
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    • 2009
  • An electric furnace, inside which desired temperatures are kept constant by generating heat, is known to be a difficult system to control and model exactly because system parameters and response delay time vary as the temperature and position are changed. In this study the heating system of ceramic drying furnaces with time-varying parameters is mathematically modeled as a second order system and control parameters are estimated by using a RIV (Recursive Instrumental-Variable) method. A modified bang-bang control with magnitude tuning is proposed in the time optimal temperature control of ceramic drying electric furnaces and its performance is experimentally verified. It is proven that temperature tracking of adaptive time optimal control using a second order model is more stable than the GPCEW (Generalized Predictive Control with Exponential Weight) and rapidly settles down by pre-estimation of the system parameters.