The estimation of the induction motor parameters by the GeTLS EXIN neuron

This paper presents a new linear neuron, the GeTLS EXIN neuron for the on-line estimation of the electrical parameters of the induction motor. This estimation problem is a non generic one, particularly for the flatness of the surface error along the K₂ direction, and current OLS neurons are not capable of facing it. Only the TLS EXIN neuron and the GeTLS EXIN neuron can cope with this issue for on-line applications. However, unlike the TLS EXIN neuron, the GeTLS EXIN neuron with its variation of the parameter ς, varies the landscape of the error surface, which then varies at each batch of data. This causes the surface to crumple up and reduce the flatness of the critical directions (K₂ in this case) with resulting improved accuracy.