Abstract
A fuzzy logic power system stabiliser has been developed using speed and active power deviations as the controller input variables. The inference mechanism of the fuzzy logic controller is represented by a 7 × 7 decision table, i.e. 49 if-then rules. In order to use it under a wide range of operating conditions, its parameters have been tuned using a neural network. The tuned stabiliser has been tested by performing non-linear simulations using a synchronous machine-infinite bus model. It is shown that the neuro-fuzzy stabiliser is superior to a fixed parameter fuzzy logic power system stabiliser.
| Original language | English |
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| Pages | 608-612 |
| Number of pages | 5 |
| Publication status | Published - 1996 |
| Event | Proceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 3 (of 3) - Taipei, Taiwan Duration: Aug 5 1996 → Aug 10 1996 |
Other
| Other | Proceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 3 (of 3) |
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| City | Taipei, Taiwan |
| Period | 8/5/96 → 8/10/96 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering