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13.11.2019 | Methodologies and Application

A robust control of a class of induction motors using rough type-2 fuzzy neural networks

verfasst von: Mohammad Hosein Sabzalian, Ardashir Mohammadzadeh, Shuyi Lin, Weidong Zhang

Erschienen in: Soft Computing | Ausgabe 13/2020

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Abstract

In this paper, a new adaptive control method is presented for a class of induction motors. The dynamics of the system are assumed to be unknown and also are perturbed by some disturbances such as variation of load torque and rotor resistance. A type-2 fuzzy system based on rough neural network (T2FRNN) is proposed to estimate uncertainties. The parameters of T2FRNN are adjusted based on the adaptation laws which are obtained from Lyaponuv stability analysis. The effects of the uncertainties and the approximation errors are compensated by the proposed control method. Simulation results verify the good performance of the proposed control method. Also a numerical comparison is provided to show the effectiveness of the proposed fuzzy system.

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Titel: A robust control of a class of induction motors using rough type-2 fuzzy neural networks
verfasst von: Mohammad Hosein Sabzalian
Ardashir Mohammadzadeh
Shuyi Lin
Weidong Zhang
Publikationsdatum: 13.11.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 13/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04493-3

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