- Tytuł:
- Cold rolling mill thickness control using the cascade-correlation neural network
- Autorzy:
-
Frayman, Y.
Wang, L.
Wan, C. - Powiązania:
- https://bibliotekanauki.pl/articles/206844.pdf
- Data publikacji:
- 2002
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
konstrukcja dynamicznej sieci neuronowej
sieć neuronowa kaskadowo-korelacyjna
sterowanie grubością walcowni zimnej
cascade-correlation neural network
cold rolling mill thickness control
direct MRAC
dynamic neural network construction - Opis:
- The improvements in thickness accuracy of a steel strip produced by a tandem cold-rolling mill are of substantial interest to the steel industry. In this paper, we designed a direct model-reference adaptive control (MRAC) scheme that exploits the natural level of excitation existing in the closed-loop with a dynamically constructed cascade-correlation neural network (CCNN) as a controller for cold rolling mill thickness control. Simulation results show that the combination of a such a direct MRAC scheme and the dynamically constructed CCNN significantly improves the thickness accuracy in the presence of disturbances and noise in comparison with to the conventional PID controllers.
- Źródło:
-
Control and Cybernetics; 2002, 31, 2; 327-342
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki
Artykuł