- Tytuł:
- Recurrent neural identification and control of a continuous bioprocess via first and second order learning
- Autorzy:
-
Baruch, I.
Mariaca-Gaspar, C. R. - Tematy:
-
backpropagation learning
direct adaptive neural control
indirect adaptive sliding mode control
Kalman filter recurrent neural network identifier
Levenberg-Marquardt learning - Pokaż więcej
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Powiązania:
- https://bibliotekanauki.pl/articles/385133.pdf Link otwiera się w nowym oknie
- Opis:
- This paper applies a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Mar quardt (L-M) learning algorithm capable to estimate para meters and states of highly nonlinear unknown plant in noisy environment. The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct and indirect adaptive neural con trol schemes. The proposed control schemes were applied for real-time recurrent neural identification and control of a continuous stirred tank bioreactor model, where fast convergence, noise filtering and low mean squared error of reference tracking were achieved.
- Dostawca treści:
- Biblioteka Nauki
Artykuł