Identification and control of a large kinescope glass furnace

Zhang, H.; Han, Chongzhao; Wan, Biao; Ren, Xiaobing

doi:10.1016/0005-1098(94)90178-3

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…[1] - [4]. In the literature, there are several methods for identification and/or control of different types of glass furnace [8]- [20]. The combined identification and control design based on empirical data for glass furnace has received little attention.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Control Design Methods for Philips Glass Furnace using Experimental Data

Magdi¹

2016

Fourth International Conference on Advances in Computing, Communication and Information Technology CCIT- 2016

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This paper describes a comparison of control system design to Philips glass furnace. The first stage considers the application of system identification techniques to obtain models using experimental data. Several models were identified, wherein the one picked up for control design has the largest level of fitness. In the second stage a set of improved control methods are implemented to design controllers based on non-adaptive (including LQR, LQGR, H 2 , H oo ) and adaptive (including MRAC, L1) methods. Simulation studies were performed and evaluated.

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Section: Introductionmentioning

confidence: 99%

A Comparison of Control Design Methods for Philips Glass Furnace using Experimental Data

Magdi¹

2016

Fourth International Conference on Advances in Computing, Communication and Information Technology CCIT- 2016

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“…12 More work on identification and control of a glass furnace itself is also available in literature. [13][14][15][16][17] To the best knowledge of the author, a previous work focusing on the product concentration control beyond the perfect mixer theory is not yet available.…”

Section: Introductionmentioning

confidence: 99%

“…Because of the long solution time of a CFD simulation which makes it difficult to be directly used for dynamic optimization purposes, efforts have been made in the reduction of CFD models for glass furnaces . More work on identification and control of a glass furnace itself is also available in literature. − To the best knowledge of the author, a previous work focusing on the product concentration control beyond the perfect mixer theory is not yet available.…”

Section: Introductionmentioning

confidence: 99%

The Optimal Product Transition In Glass Furnaces

2009

Ind. Eng. Chem. Res.

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Product change in glass furnaces is a common and challenging industrial problem generally associated with long transition times and possible ream defects. A reduction in the product turnover time implies a higher product yield and a reduced energy consumption. This turnover time relies to a large extent on the understanding of furnace dynamics. In this work, the disadvantages of the current transition practice (based on the concepts of minimum residence time and perfect mixing) are discussed. An optimization approach that is based on the residence time distribution of the glass furnace is tailored to accommodate practical implementation issues in the product transition control. Comparisons of the current transition practice and the proposed approach are made through computer simulations, which demonstrate that significant savings in the product turnover time are expected if the latter is used.

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Identification and control of a large kinescope glass furnace

Cited by 2 publications

References 2 publications

A Comparison of Control Design Methods for Philips Glass Furnace using Experimental Data

A Comparison of Control Design Methods for Philips Glass Furnace using Experimental Data

The Optimal Product Transition In Glass Furnaces

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