| 基于模糊ARMAX模型的模糊建模 |
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| 引用本文： | 王宏伟,于双和.基于模糊ARMAX模型的模糊建模[J].控制理论与应用,2009,26(1):85-88. |
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| 作者姓名： | 王宏伟 于双和 |
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| 作者单位： | 1. 大连理工大学电信学院,辽宁,大连,116023
2. 大连海事大学自动化与电气学院,辽宁,大连,116023 |
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| 基金项目： | 国家自然科学基金资助项目(60674061). |
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| 摘 要： | 提出了一种利用MGS(modified Gram-Schmidt)算法建立模糊ARMAX模型的方法, 给出了基于MGS算法的模型结构和参数辨识的一体化方法. 利用MGS正交变换对通过GK模糊聚类的聚类结果进行变换, 确定对模型贡献大的规则, 删除对模型贡献小的规则, 同时对模型中的参数进行估计. 本文提出的方法能够实现模糊模型的结构和参数的优化. 仿真结果表明, 本文提出的方法能够建立非线性系统的模糊ARMAX模型.
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| 关 键 词： | 模糊建模 GK模糊聚类 辨识 正交变换 |
| 收稿时间： | 2007/6/19 0:00:00 |
| 修稿时间： | 2008/4/17 0:00:00 |
Fuzzy modeling based on fuzzy ARMAX model |
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| WANG Hong-wei and YU Shuang-he.Fuzzy modeling based on fuzzy ARMAX model[J].Control Theory & Applications,2009,26(1):85-88. |
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| Authors: | WANG Hong-wei and YU Shuang-he |
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| Affiliation: | School of Information and Electrical Engineering, Dalian University of Technology, Dalian Liaoning 116023, China;School of Automation and Electrical Engineering, Dalian Maritime University, Dalian Liaoning 116023, China |
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| Abstract: | The MGS (modified Gram-Schmidt) algorithm is proposed to construct the fuzzy ARMAX model. An integrated algorithm for structure identification and parameter identification of fuzzy model is given based on MGS algorithm. The result from GK fuzzy clustering is transformed to confirm the important rules and to remove the less important rules by means of MGS transformation. The parameters of fuzzy model are estimated via the proposed method; and the structure and parameters of fuzzy model are optimized. Simulation results show that the fuzzy ARMAX model of non-linear system can be built by the proposed algorithm. |
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| Keywords: | fuzzy modeling GK fuzzy clustering identification orthogonal transforms |
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