Abstract
The application of fuzzy clustering techniques has recently become in a very useful alternative in the area of modeling and identification of complex industrial processes. In particular, fuzzy clustering techniques such as Fuzzy C-Means and the Gustafson-Kessel (GK) algorithms will be analyzed and applied in details in this paper. These algorithms will be implemented in the construction of Takagi-Sugeno fuzzy models for the gas-liquid separation process, the water-oil separation process and the oil-heating process, which are important processes in the oil industry. Validations of the obtained fuzzy models will be performed and some conclusions will be established.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 159-171 |
| Number of pages | 13 |
| Journal | WSEAS Transactions on Systems and Control |
| Volume | 3 |
| Issue number | 3 |
| State | Published - 2008 |
| Externally published | Yes |
Keywords
- Artificial lift production methods
- Fuzzy C-means
- Fuzzy clustering
- Gustafson-Kessel (GK) algorithm
- Least-squares method
- Production separator
- Washing-tanks and fired heaters
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization