scholarly journals Current Control of Switched Reluctance Motor Using Self-tuning Fuzzy Controller

2016 ◽  
Vol 17 (3) ◽  
pp. 473-479
Author(s):  
Young-Soo Lee ◽  
Jaehyuck Kim ◽  
Hun Oh
Keyword(s):  
Fuzzy Controller ◽  
Switched Reluctance Motor ◽  
Current Control ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Self Tuning

Self-Tuning Fuzzy Controller Design for a Switched Reluctance Motor Drive System

2013 ◽  
Vol 418 ◽  
pp. 100-103
Author(s):  
Shun Yuan Wang ◽  
Chwan Lu Tseng ◽  
Shou Chuang Lin ◽  
Jen Hsiang Chou ◽  
Yu Wen Chen ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Control Theory ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Switched Reluctance Motor ◽  
Drive System ◽  
Electromagnetic Torque ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Self Tuning

This study adopts the fuzzy control theory to design a self-tuning fuzzy controller (STFC), which allows adjustment to overcome the controller design difficulty caused by switched reluctance motor (SRM) nonlinearity. Based on the torque sharing function (TSF), the proposed STFC was implanted into an SRM direct torque control (DTC) drive system to develop a system with superior speed and electromagnetic torque dynamic responses. In addition, the control strategy possessed excellent electromagnetic torque response, and effectively improved the dynamic response of the system. Keywords: fuzzy control theory, switched reluctance motor (SRM), torque sharing strategy.

scholarly journals Adaptive neuro-fuzzy controller of switched reluctance motor

2007 ◽  
Vol 4 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Ahmed Tahour ◽  
Hamza Abid ◽  
Ghani Aissaoui
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Expert Knowledge ◽  
Digital Simulation ◽  
Switched Reluctance Motor ◽  
Motor Speed ◽  
Inference System ◽  
Switched Reluctance ◽  
Neuro Fuzzy ◽  
Reluctance Motor

This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI).

Self-tuning control for current loop in a Switched Reluctance Motor drive

2011 ◽  
Author(s):  
Laurinda L. N. dos Reis ◽  
Romulo N. Almeida ◽  
Wellington A. Silva ◽  
Gabriela de M. P. Mendes ◽  
Otacilio M. Almeida
Keyword(s):  
Switched Reluctance Motor ◽  
Motor Drive ◽  
Current Loop ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Self Tuning
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