| 引用本文: | 张平安,李人厚,张金明.复杂系统的递阶模糊辨识[J].控制理论与应用,2002,19(1):99~102.[点击复制] |
| ZHANG Ping'an,LI Renhou,ZHANG Jinming.Hierarchical Fuzzy Identification for Complex Systems[J].Control Theory and Technology,2002,19(1):99~102.[点击复制] |
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| 复杂系统的递阶模糊辨识 |
| Hierarchical Fuzzy Identification for Complex Systems |
| 摘要点击 1757 全文点击 1054 投稿时间：1999-06-23 修订日期：2001-05-18 |
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| DOI编号 10.7641/j.issn.1000-8152.2002.1.020 |
| 2002,19(1):99-102 |
| 中文关键词 模糊辨识 递阶模糊模型 系统辨识 |
| 英文关键词 fuzzy identification hierarchical fuzzy model system identification |
| 基金项目 国家自然科学基金(69174018)资助项目 |
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| 中文摘要 |
| 针对Takagi_Sugeno模糊模型 (T_S模型 )严重的维数灾问题, 借鉴GMDH算法, 提出了一种新的复杂系统递阶模糊辨识方法. 本文首先详细描述了由两输入变量的特殊T_S模型所组成的递阶模糊模型 ;然后提出了具体的辨识该递阶模糊模型的方法. 该方法的特点是 :a)在结构辨识阶段, 用FCM模糊聚类方法评价系统中每个输入变量的重要性, 以便构造合理的递阶模糊模型 ;b)预先合理地确定了所要辨识的参数的初始值, 用扩展卡尔曼滤波方法可很快地得到这些参数. 最后, 给出的仿真实例说明了本文辨识方法的有 |
| 英文摘要 |
| Drawn ideas from GMDH algorithm, a new approach to hierarchical fuzzy identification for complex systems is presented to overcome the serious limitation of Takagi and Sugeno's model (T_S model), that is the problem of "curse of dimensionality". Firstly, a new hierarchical fuzzy model, which consists of a number of hierarchically connected special T_S type models with two input variables, is described in detail. Then, a concrete method for identifying the hierarchical fuzzy model is also proposed. The main features of the presented method are: a) Fuzzy C_means (FCM) is used to evaluate the significance of each input variable for rationally constructing the hierarchical model in the stage of structure identification; b) Since parameters to be identified are properly determined in advance, they can be obtained rapidly by using extended Kalman filter algorithms. Finally, an example is given to demonstrate the validity of the approach. |
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