控制理论与应用2000，Vol.17Issue(3)：419-422,4.
基于模糊规则的非线性系统建模方法
Nonlinear Systems Modeling via Fuzzy Logic Rules
王宏伟 1马广富2
作者信息
- 1. 国防科学技术大学自动控制系,长沙,410073
- 2. 哈尔滨工业大学仿真中心,哈尔滨,150001
- 折叠
摘要
Abstract
We propose a new self-tuning fuzzy modeling by means of fuzzy clustering. Based on fuzzy clustering, the adaptive fuzzy inference is used to modify the fuzzy system. Moreover, based on this modified fuzzy system, the paper presents an on-line identifying algorithm with which the on-line parameter estimation of nonlinear system is realized. To demonstrate the applicability of the proposed method, simulation results relative to a few examples are presented in the end.关键词
系统辨识/模糊系统/非线性系统建模/递推模糊聚类/卡尔曼滤波算法/在线辩识Key words
system identification/fuzzy systems/nonlinear system modeling/recursive fuzzy clustering/Kalman filtering algorithm/on-line identification分类
信息技术与安全科学引用本文复制引用
王宏伟,马广富..基于模糊规则的非线性系统建模方法[J].控制理论与应用,2000,17(3):419-422,4.
