A Neural Controller for Induction Motors: Fractional-Order Stability Analysis and Online Learning Algorithm

Alattas, Khalid A.; El-Sousy, Fayez F. M.; Mobayen, Saleh; Mai The Vu; Aredes, Mauricio

Abstract

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and are perturbed by the variation of rotor resistance and load changes. The control system has two stages. In the identification stage, the group method of data-handling (GMDH) neural network (NN) was designed for online modeling of the IM. In the control stage, the GMDH-NN was applied to compensate for the impacts of disturbances and uncertainties. The stability is shown by the Lyapunov approach. Simulations demonstrated the good accuracy of the suggested new control approach under disturbances and unknown dynamics.

Más información

Título según WOS: ID WOS:000774067600001 Not found in local WOS DB
Título de la Revista: MATHEMATICS
Volumen: 10
Número: 6
Editorial: MDPI
Fecha de publicación: 2022
DOI:

10.3390/math10061003

Notas: ISI