摘要
提出用一种改进的T-S模型实现非线性系统在线辨识的算法。通过样本与聚类中心矢量之间的贴近度来修正聚类中心,并根据样本到中心矢量的距离对输入数据空间进行划分。在此基础上利用递推最小二乘算法辨识出模型的结论参数。给出了具体的算法步骤,将该方法与其他模糊辨识方法进行比较。结果表明,该方法具有简单、实用、辨识精度高等优点。
A new way of on-line identification based on an improved T-S model is presented. The clustering centre vectors are updated by the close degree, which indicates the relation between input vectors and clustering centre. The input data space is partitioned into some local regions by the distance between input data and clustering centre. The conclusion parameters are identified by the recursive least-square identification algorithm. The concrete steps of the algorithm ale given. It is applied to identify the T-S model of the Box-Jenkins model and a coordinated control system of 300 MW unit. The computational results show that this on-line identifier is effective.
出处
《华北电力大学学报（自然科学版）》
CAS
北大核心
2005年第6期14-17,共4页
Journal of North China Electric Power University：Natural Science Edition
关键词
在线辨识
T-S模型
热工过程
模糊辨识
on-line identification
T-S fuzzy model
thermal.process
fuzzy identification
