Nonlinear system identification using a neo fuzzy neuron algorithm: electrical drive application
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Updated: Oct 18, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
R P Landim1, B R de Menezes, S R Silva
1Universitária Recife PE-Brasil. REGIS@NOVELL.CPDEE.UFMG.BR
Abstract:
This work presents a Neo-Fuzzy-Neuron algorithm for the identification of nonlinear dynamic systems at the point of view of a rotor flux observer. The algorithm training is on-line, has low computational cost, does not require previous training and its convergence in one step is proved. The gradient descent method is used for its weights adjustment. Simulation and experimental results demonstrate the effectiveness of the algorithm for flux observer of induction motor drive system.
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