Poznyak, Alexander S. ; Yu, Wen ; Sanchez, Edgar N. ; Sira-Ramirez, Hebertt
Adaptive Learning and Control Using Sliding Modes
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
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 8, number 1 (1998) ; click here to follow the link
Biblioteka Uniwersytetu Zielonogórskiego
Sep 3, 2021
Dec 18, 2020
116
https://www.zbc.uz.zgora.pl/publication/64638
Edition name | Date |
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Robust identification by dynamic neural networks using sliding mode learning | Sep 3, 2021 |
Korbicz, Józef - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Beliczyński, Bartłomiej - red.