| 基于RBF神经网络陶瓷窑炉温度动态矩阵控制 |
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| 引用本文： | 刘伟,王思明,张国武.基于RBF神经网络陶瓷窑炉温度动态矩阵控制[J].中国陶瓷,2010(9). |
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| 作者姓名： | 刘伟 王思明 张国武 |
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| 作者单位： | 兰州交通大学自动化与电气工程学院; |
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| 基金项目： | 甘肃省自然科学研究基金项目,编号:0916RJZA051 |
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| 摘 要： | 陶瓷窑炉普遍具有纯滞后、大惯性、非线性、时变复杂等特点,其精确数学模型往往很难获取。针对这类系统,本文采用RBF神经网络建立被控对象模型,避免了常规控制算法建立对象精确数学模型的困难。应用动态矩阵预测算法实现对被控系统的预测控制。该控制方法具有很好的动、静态性能和强鲁棒性。以陶瓷窑炉温度为对象,与PID控制进行了比较;仿真结果证明了所提控制方法的有效性。
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| 关 键 词： | 陶瓷窑炉 RBF神经网络 动态矩阵控制 温度 |
DYNAMIC MATRIX CONTROL OF CERAMICS KILN TEMPERATURE BASED ON RBF NETWORK |
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| Liu Wei,Wang Siming,Zhang Guowu.DYNAMIC MATRIX CONTROL OF CERAMICS KILN TEMPERATURE BASED ON RBF NETWORK[J].China Ceramics,2010(9). |
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| Authors: | Liu Wei Wang Siming Zhang Guowu |
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| Affiliation: | Liu Wei,Wang Siming,Zhang Guowu(School of Automation and Electrical Engineering,Lanzhou Jiao Tong University,Lanzhou 730070) |
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| Abstract: | In general,the ceramic kiln has features of purely hysteretic,big inertness,nonlinear and complexity.Its accurate mathematics model is usually very difficult to be obtained.So for this sort system,in this paper the model of the controlled plant is built by RBF network.This method depends on no accurate mathematics model of the controlled object,so avoid the difficulties.The dynamic matrix control(DMC) algorithm is employed to implement the predictive control of the controlled plant.Both of the dynamic and s... |
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| Keywords: | ceramics kiln RBF network dynamic matrix control temperature |
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