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

Authors :
Sabzalian, Mohammad Hosein
Mohammadzadeh, Ardashir
Lin, Shuyi
Zhang, Weidong
Source :
Soft Computing - A Fusion of Foundations, Methodologies & Applications. Jul2020, Vol. 24 Issue 13, p9809-9819. 11p.
Publication Year :
2020

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14327643
Volume :
24
Issue :
13
Database :
Academic Search Index
Journal :
Soft Computing - A Fusion of Foundations, Methodologies & Applications
Publication Type :
Academic Journal
Accession number :
143476933
Full Text :
https://doi.org/10.1007/s00500-019-04493-3