| Optimal control of end-port glass tank furnace regenerator temperature based on artificial neural network |
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| 作者姓名： | 陈希 |
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| 作者单位： | Department of |
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| 摘 要： | 1 Introduction1 The principle controlled target of an end-port glass tank furnace regenerator is the melting temperature which is regulated by the flow of oil or gas. The disturbances stem from feed-in glass powder, the pressure, value and atomization of fuel, the secondary wind, the tank furnace pressure, etc. Among them, some can be controlled and some cannot. In order to keep the temperature steady, a cascade ratio regulating system is designed, in which the temperature adjustment functions…
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| 关 键 词： | B-P网络 拓扑结构 优化设计 神经网络 |
Optimal control of end-port glass tank furnace regenerator temperature based on artificial neural network |
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| CHEN Xi,ZHAO Guo-Zhu.Optimal control of end-port glass tank furnace regenerator temperature based on artificial neural network[J].Journal of Chongqing University,2005,4(2):113-116. |
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| Authors: | CHEN Xi ZHAO Guo-Zhu |
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| Abstract: | In the paper, an artificial neural network (ANN) method is put forward to optimize melting temperature control, which reveals the nonlinear relationships of tank melting temperature disturbances with secondary wind flow and fuel pressure, implements dynamic feed-forward complementation and dynamic correctional ratio between air and fuel in the main control system. The application to Anhui Fuyang Glass Factory improved the control character of the melting temperature greatly. |
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| Keywords: | B-P network topology structure learning efficiency momentum modulus artificial neural network based melting temperature regenerator furnace tank glass control system application Anhui Glass Factory improved character complementation dynamic ratio nonlinear relationships secondary |
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