Adaptive sliding-mode type-2 neuro-fuzzy control of an induction motor

2015 ◽  
Vol 42 (19) ◽  
pp. 6635-6647 ◽  
Author(s):  
Saleh Masumpoor ◽  
Hamid yaghobi ◽  
Mojtaba Ahmadieh Khanesar
Keyword(s):  
Fuzzy Control ◽  
Induction Motor ◽  
Sliding Mode ◽  
Adaptive Sliding Mode ◽  
Neuro Fuzzy

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator

2012 ◽  
Vol 60 (1) ◽  
pp. 61-70 ◽  
Author(s):  
T. Orlowska-Kowalska ◽  
M. Dybkowski
Keyword(s):  
Induction Motor ◽  
Sliding Mode ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Adaptive Sliding Mode ◽  
Speed Controller ◽  
Neuro Fuzzy ◽  
On Line ◽  
Speed Estimator ◽  
Model Reference Adaptive

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct rotor-field oriented control (DRFOC) of the induction motor (IM) drive structure. Connective weights of the controller are trained on-line according to the error between the actual speed of the drive and the reference model output signal. The rotor flux and speed of the vector controlled induction motor are estimated using the model reference adaptive system (MRAS) - type estimator. Presented simulation results are verified by experimental tests performed on the laboratory-rig with DSP controller.

Type-2 Neuro-Fuzzy Control for a Class of Nonlinear Systems

2021 ◽  
Author(s):  
Shixi Hou ◽  
Cheng Wang ◽  
Suwei Zhai ◽  
Yundi Chu
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Control ◽  
Neuro Fuzzy
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