Name
Abstract | ||
|---|---|---|
Fuzzy Control provides a good support to translate the knowledge of a skilled plant operator into rules, making intelligent control possible. But it is difficult to represent the expert's knowledge with no degradation, so a tuning phase is required. This is not an easy task, and there is not a general procedure for it. On the other hand, most of the control systems are still based on the conventional PID regulator. Aström has developed an empirical tool to predict the achievable performance of these controllers and to assess whether they are properly tuned. Based on Buckley's results, that have analytically proved the equivalence between one of the simplest fuzzy logic controller (FLC) and a PI, it is possible to apply Aström's tool to evaluate the performance of a FLC. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1007/3-540-61478-8_78 | CAST |
Keywords | Field | DocType |
self-tuning,tuning fuzzy logic controllers,classical techniques,expert control,tuning fuzzy controllers,fuzzy control,pid control,adpative control.,intelligent control,control system | Intelligent control,Fuzzy electronics,Neuro-fuzzy,PID controller,Control theory,Computer science,Fuzzy logic,Control system,Fuzzy control system,Adaptive neuro fuzzy inference system | Conference |
ISBN | Citations | PageRank |
3-540-61478-8 | 1 | 0.35 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matilde Santos | 1 | 143 | 24.39 |
| S. Dormido | 2 | 90 | 11.44 |
| A. P. de Madrid | 3 | 15 | 2.95 |
| Fernando Morilla | 4 | 82 | 14.91 |
| Jesús Manuel De La Cruz | 5 | 373 | 25.35 |