Self-organizing fuzzy intelligent system

被引:0
|
作者
Li, CS [1 ]
Lee, CY [1 ]
机构
[1] Chang Gung Univ, Dept Elect Engn, Tao Yuan 333, Taiwan
关键词
clustering; fuzzy control; inverse learning control; random optimization; self-learning; self-organization; temperature control;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A self-organizing fuzzy system (SOFS) is presented. A plant model is not required for training, that is, the plant model is unknown to the SOFS. Using new data types, the vectors and matrices, a concise formulation is developed for the organization process and the inference activities of the SOFS. The fuzzy system can learn its rule-based structure and parameters from input/output training data. There is no fuzzy IF-THEN rule in the system initially. The fuzzy control policy is constructed automatically during learning process when the system is simulated by input/output training data. With the well-known random optimization (RO) method, the generated fuzzy system can learn its parameters for specific applications. The proposed SOFS is applied on temperature control problem.
引用
收藏
页码:473 / 477
页数:5
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