Abstract
The application of fuzzy sets theory in process data filtering was discussed. A fuzzy approach for system identification and state estimation was developed. Analysis showed that the fuzzy-data based estimator (FBE) provided better performance than those of various modified Kalman filter (KF) without the need of priori information on the nature of noise.
| Original language | English |
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| Pages | 325-330 |
| Number of pages | 6 |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | The IEEE International conference on Fuzzy Systems - St. Louis, MO, United States Duration: 2003 May 25 → 2003 May 28 |
Conference
| Conference | The IEEE International conference on Fuzzy Systems |
|---|---|
| Country/Territory | United States |
| City | St. Louis, MO |
| Period | 2003/05/25 → 2003/05/28 |
Keywords
- Filtering
- Fuzzy sets theory
- Kalman filter
- Takagi-Sugeno (T-S) fuzzy model
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics