一种基于扩张原理的模糊模型及其辨识方法
An Extension-Principle-Based Fuzzy Model and its Identification Algorithm
-
摘要: 提出一种新的基于LR型模糊数及其运算的模糊模型结构--扩展的TSK模型 (ETSK模型).借助于LR型模糊数隶属函数图形的面积和重心横坐标这两个"数字特征", 导出了ETSK模型的输入输出解析表达式,并证明了ETSK模型与变权TSK模型的等价关 系,同时给出一种对ETSK模型规则后件的参数辨识方法.仿真辨识实验结果表明,ETSK模 型的辨识效果和预报精度更优.Abstract: An extended TSK model--ETSK model, based on LR type fuzzy numbers and their extended operations, is proposed in this paper. The input-output analytic expression is proved and a parameter identification algorithm is also constructed to identify the areas and gravity centers of the membership functions of LR type fuzzy numbers. A kind of variable weight TSK model which is equivalent to the ETSK model is also deduced. Simulation shows that the ETSK model can give out more accurate long-range predictions than an LM model and a TSK model.
-
Key words:
- Fuzzy identification /
- LM models /
- TSK models /
- ETSK models
-
计量
- 文章访问数: 2067
- HTML全文浏览量: 68
- PDF下载量: 1125
- 被引次数: 0
下载:
