Abstract
This paper discusses a new approach to design a fuzzy logic control system, based on the self-organizing map (SOM) neural network. SOM is used to generate multivariate fuzzy state space from system's input-output data through unsupervised training. The trained SOM is then used as a part of an inference mechanism for a fuzzy logic controller. The proposed method is compared with other fuzzy/NN approaches. Sample data from a chemical plant is used to demonstrate the technique.
| Original language | English (US) |
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| Title of host publication | IEEE International Conference on Fuzzy Systems |
| Publisher | IEEE Computer Society |
| Pages | 70-75 |
| Number of pages | 6 |
| Volume | 1 |
| State | Published - 1994 |
| Event | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA Duration: Jun 26 1994 → Jun 29 1994 |
Other
| Other | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) |
|---|---|
| City | Orlando, FL, USA |
| Period | 6/26/94 → 6/29/94 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality