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

被引：9
|
作者：
Sabzalian, Mohammad Hosein [1 ]
Mohammadzadeh, Ardashir [2 ]
Lin, Shuyi [1 ,3 ]
Zhang, Weidong [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Univ Bonab, Dept Elect Engn, Bonab, Iran
[3] Purdue Univ, Sch Ind Engn, W Lafayette, IN 47907 USA
来源：
SOFT COMPUTING | 2020年 / 24卷 / 13期
基金：
美国国家科学基金会; 国家重点研发计划;
关键词：
Induction motor; Rough neural network; Type-2 fuzzy systems; Robust stability analysis; Faulty conditions; SLIDING MODE CONTROL; SPEED CONTROL; SYSTEMS;
D O I：
10.1007/s00500-019-04493-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：9809 / 9819
页数：11
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