| 基于神经网络的加氢反应器温度优化控制 |
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| 引用本文： | 郑明方,史国栋,薛国新,王洪元.基于神经网络的加氢反应器温度优化控制[J].计算机仿真,2002,19(6):44-45,64. |
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| 作者姓名： | 郑明方 史国栋 薛国新 王洪元 |
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| 作者单位： | 江苏石油化工学院,江苏,常州,213016 |
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| 基金项目： | 教育部高校骨干教师资助计划资助 (江苏省 5 8号 ) |
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| 摘 要： | 根据加氢反应器的特点，提出了一种加氢反应器出口温度神经元网络优化控制方法，给出了作为模型预估器的神经网络GA－BP算法流程及GA算法实现，提出了最优控制指标选择原则及控制指标表达式，经计算机对四床层一段加氢裂化装置进行仿真研究表明，该控制方法具有良好的跟踪性能及抗干扰能力。
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| 关 键 词： | 神经网络 加氢反应器 温度优化控制 计算机仿真 石油 |
| 文章编号： | 1006-9348(2002)06-0044-02 |
The Neural Network Optimization Control Strategy For Catalytic Hydrogen |
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| ZHENG Ming-fang,SHI Guo-dong,XUE Guo-xin,WANG Hong-yuan.The Neural Network Optimization Control Strategy For Catalytic Hydrogen[J].Computer Simulation,2002,19(6):44-45,64. |
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| Authors: | ZHENG Ming-fang SHI Guo-dong XUE Guo-xin WANG Hong-yuan |
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| Abstract: | According to the characteristic of the pipeline cracking furnace, a new neural network optimization control strategy of hydrogen reactor's output temperature is put forward. The GA-BP learning algorithm of neural network, the GA learning algorithm, the rule of optimum control including their features were introduced. The computer simulation prove that the anti-jamming capacity and the track performance of the strategy is all right |
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| Keywords: | Pipeline cracking furnace Neural network Temperature control |
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