摘要
基于模糊集合的模糊模型,利用模糊推理规则描述复杂、病态、非线性系统是一种有效方法.本文提出了利用目标函数确定非线性系统的结构和参数的方法.首先,通过Gustafson-Kessel(GK)模糊聚类确定模型结构.然后,通过目标函数与参数估计一起进行递推计算,进而实现对模糊模型结构简化,删除冗余规则.结构确定过程中采用了UD矩阵分解方法,大大降低了计算量.仿真结果证明了提出方法的有效性.
For dynamic systems with complex,ill-conditioned or nonlinear characteristics,the fuzzy modeling method based on fuzzy sets is very effective to describe the properties of the systems.By using objective function,we propose a new algorithm to confirm the structure and parameters of fuzzy model for nonlinear systems.First,the structure of fuzzy model is confirmed by using Gustafson-Kessel(GK)fuzzy clustering;and then,the objective function and parameter estimation are simultaneously employed in recursive calculations to simply the model structure and delete redundant rules.The UD matrix decomposition is used to reduce the amount of computation in the determination process of fuzzy model.The simulation results demonstrate the effectiveness of the proposed method.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2010年第4期523-526,共4页
Control Theory & Applications
基金
国家自然科学基金资助项目(60674061)
关键词
模糊模型
GK模糊聚类
目标函数
UD矩阵分解
fuzzy model
GK fuzzy clustering
objective function
UD matrix decomposition