Autor:
Poznyak, Alexander S. ; Yu, Wen ; Sanchez, Edgar N. ; Sira-Ramirez, Hebertt
Współtwórca:
Tytuł:
Robust identification by dynamic neural networks using sliding mode learning
Podtytuł:
Adaptive Learning and Control Using Sliding Modes
Tytuł publikacji grupowej:
Temat i słowa kluczowe:
sterowanie ; sterowanie-teoria ; sztuczna inteligencja ; matematyka stosowana ; informatyka
Abstract:
The problem of identification of continuous, uncertain nonlinear systems in the presence of bounded disturbances is implemented using dynamic neural networks. The proposed neural identifier guarantees a bound for the state estimation error. This bound turns out to be a linear combination of internal and external uncertainty levels. ; The neural net weights are updated on-line by a learning algorithm based on the sliding mode technique. To the best of the authors' knowledge, such a learning scheme is proposed for dynamic neural networks for the first time. Numerical simulations illustrate its effectiveness, even for highly nonlinear systems in the presence of important disturbances
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Data wydania:
Typ zasobu:
Strony:
Źródło:
AMCS, volume 8, number 1 (1998) ; kliknij tutaj, żeby przejść