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.
| 原文 | 英語 |
|---|---|
| 頁（從 - 到） | 473-477 |
| 頁數 | 5 |
| 期刊 | Conference Record - IAS Annual Meeting (IEEE Industry Applications Society) |
| 卷 | 1 |
| 出版狀態 | 已出版 - 2002 |
| 事件 | 37th IAS Annual Meeting and World Conference on Industrial applications of Electrical Energy - Pittsburgh, PA, 美國 持續時間: 13 10 2002 → 18 10 2002 |