| 引用本文: | 刘福才, 关新平, 裴 润.基于一种新模糊模型的非线性系统模糊辨识[J].控制理论与应用,2003,20(1):113~116.[点击复制] |
| LIU Fu-cai, GUAN Xin-ping, PEI Run.Fuzzy identification based on new fuzzy model for nonlinear systems[J].Control Theory and Technology,2003,20(1):113~116.[点击复制] |
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| 基于一种新模糊模型的非线性系统模糊辨识 |
| Fuzzy identification based on new fuzzy model for nonlinear systems |
| 摘要点击 1453 全文点击 2343 投稿时间：2001-04-04 修订日期：2001-12-20 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.1.026 |
| 2003,20(1):113-116 |
| 中文关键词 模糊建模 模糊if-then规则 加权递推最小二乘算法 启发式方法 |
| 英文关键词 fuzzy modeling fuzzy if-then rules WRLSA heuristic method |
| 基金项目 国家杰出青年基金(69925308); 黑龙江省自然科学基金资助项目 |
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| 中文摘要 |
| 提出一种基于新的模糊模型和加权递推最小二乘算法 (WRLSA)的非线性系统模糊辨识方法.新型的具有插值能力的模糊系统可以通过学习从输入输出采样数据中提取MISO系统模糊规则,它继承了Sugeno模型及其变化形式的许多优点.采用相应的模糊隶属函数,使得被辨识的模型可用若干局部线性模型来表示,然后利用WRLSA拟合这些线性模型.给出了详细的模糊辨识算法,为了验证该辨识方法的有效性,还给出了对熟知的Box-Jenkins数据的辨识结果. |
| 英文摘要 |
| A fuzzy identification method for nonlinear systems is suggested based on a new fuzzy model and weighted recursive least square algorithm (WRLSA). The new fuzzy system with interpolating capability extracts fuzzy rules of MISO system from input-output sample data through learning, and inherits many merits from Sugeno-type models and their variations. Through using suitable fuzzy membership function, the identified fuzzy model can be described by several local linear models. And finally, WRLSA is used to fit these linear models. The new fuzzy identification algorithm is proposed. To demonstrate availability of the identification method, the well-known Box-Jenkins data set is also identified. |
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