| 基于系统辨识与T-S模糊神经网络的磨矿分级控制 |
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| 引用本文： | 赵宏伟,齐一名,臧雪柏,张孝临,马英喆. 基于系统辨识与T-S模糊神经网络的磨矿分级控制[J]. 吉林大学学报(工学版), 2011, 41(1): 171-0175 |
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| 作者姓名： | 赵宏伟 齐一名 臧雪柏 张孝临 马英喆 |
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| 作者单位： | 1. 吉林大学,计算机科学与技术学院,长春130012;吉林大学符号计算与知识工程教育部重点实验室,长春,130012
2. 吉林大学,计算机科学与技术学院,长春130012 |
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| 基金项目： | “十一五”国家科技支撑计划项目（2006BAC21B01）；鞍钢集团科技攻关计划项目（2007科A23）. |
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| 摘 要： | 针对磨矿分级过程控制中具有的慢时变、非线性特征,提出了一种基于系统辨识的自适应模糊推理网络模型,并应用于磨矿控制领域.利用模糊聚类法对现有数据样本进行系统辨识,自动获取模糊规则库和相应的初始参数.依据得到的模糊系统构建基于Takage-Sugeno推理模型的自适应模糊神经网络推理系统,获得比传统的模糊神经网络具有更强的...
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| 关 键 词： | 人工智能 模糊神经网络 系统辨识 自适应控制 磨矿分级控制 |
| 收稿时间： | 2009-11-26 |
Control of milling classification using system identification and T-S fuzzy neural network |
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| ZHAO Hong-wei,QI Yi-ming,ZANG Xue-bai,ZHANG Xiao-lin,MA Ying-zhe. Control of milling classification using system identification and T-S fuzzy neural network[J]. Journal of Jilin University:Eng and Technol Ed, 2011, 41(1): 171-0175 |
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| Authors: | ZHAO Hong-wei QI Yi-ming ZANG Xue-bai ZHANG Xiao-lin MA Ying-zhe |
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| Affiliation: | 1.College of Computer Science and Technology,Jilin University, Changchun 130012,China;2.Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012,China |
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| Abstract: | Milling classification control is a slow time-delaying and nonlinear process. A control method was presented based on fuzzy neural network. To automatically acquire the fuzzy rules and the initial parameters of the algorithm, the fuzzy clustering was used in system identification. According to the received fuzzy system, an adaptive-network based fuzzy inference system was built on Takage-Sugone inference model with no professional experience, the capability of which is more adaptive and faster than traditio... |
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| Keywords: | artificial intelligence fuzzy neural network system identification adaptive control milling classification control |
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