| 引用本文: | 张小刚, 陈华, 章兢, 刘小燕.基于图像反馈的回转窑烧结温度智能预测控制[J].控制理论与应用,2007,24(6):995~998.[点击复制] |
| ZHANG Xiao-gang, CHEN Hua, ZHANG Jing, LIU Xiao-yan.Intelligent predictive control strategy applied to sintering temperature in rotary kiln based on image feedback[J].Control Theory and Technology,2007,24(6):995~998.[点击复制] |
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| 基于图像反馈的回转窑烧结温度智能预测控制 |
| Intelligent predictive control strategy applied to sintering temperature in rotary kiln based on image feedback |
| 摘要点击 1791 全文点击 1914 投稿时间：2005-04-25 修订日期：2006-11-10 |
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| DOI编号 10.7641/j.issn.1000-8152.2007.6.026 |
| 2007,24(6):995-998 |
| 中文关键词 预测控制 回转窑 过程控制 图像处理 遗传算法 神经网络 |
| 英文关键词 predictive control rotary kiln process control image processing genetic algorithm neural network |
| 基金项目 湖南省自然科学基金资助项目(04JJ3011); 湖南省重点科研项目(05GK2003); 国家自然科学基金重点资助项目(60634020); 国家自然科学基金资助项目(50704016) |
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| 中文摘要 |
| 利用火焰图像作为回转窑烧结温度的反馈信号参与闭环预测控制, 融合现场热工信号, 设计了烧结温度的RBF网络预测模型, 并利用遗传算法进行滚动优化, 现场运行结果表明该方法可在正常工况下对烧结温度进行稳定控制. |
| 英文摘要 |
| The sintering temperature in rotary kiln is measured through image processing algorithm as feedback of its predictive control. The predictive model based on RBF network is designed by the image and other process data optimized by genetic algorithm. The final results of application at an alumina sintering kiln show that this intelligent predictive control strategy can achieve higher stability in normal condition. |