Wheel Slip Regulation Using Fuzzy Spiking Neural Networks
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, a fuzzy spiking neural network structure is developed for the wheel slip regulation problem of an Antilock Braking System. Sliding mode control theory is utilized in the derivation of the update rules for the neural network's weights as well as the parameters of the fuzzy membership functions. Gaussian membership functions are used to convert the sensor readings into the neural networks inputs and the spike response model is employed to denote the effect of the incoming spikes on the postsynaptic membrane potential. The use of the Lyapunov stability method for the derivation of the parameter update rules leads to a stable system response even in the existence of external disturbances.
Açıklama
International Joint Conference on Neural Networks (IJCNN) -- JUL 24-29, 2016 -- Vancouver, CANADA
Anahtar Kelimeler
Kaynak
2016 International Joint Conference on Neural Networks (Ijcnn)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
