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.

Fuzzy Control Technology for Drive System of Switched Reluctance Motor

2011 ◽  
Vol 383-390 ◽  
pp. 285-289
Author(s):  
Guan Qun Sun ◽  
Bin Rui Wang
Keyword(s):  
Fuzzy Control ◽  
Electric Power ◽  
Switched Reluctance Motor ◽  
Drive System ◽  
Random Disturbance ◽  
Control Technology ◽  
Nonlinear Parameters ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Designed Experiment

A fuzzy self-correction controller based on DSP (TMS320LF240) micro-controller was designed to solve the problem that traditional controller can’t meet the random disturbance parameters of reluctance motor having notable nonlinear. Parameters could be automatically adjusted and response is rapid. According to the demand that two windings provide electric power at the same time for switched reluctance motor (SR motor), the system adopted Mamdani model with two inputs, MAXMIN barycenter technique was used for judging manner. Fuzzy research table and driving software were designed. Experiment results with a 5.5KW SR motor illustrated that the four phases SRD with fuzzy control technology proposed in this paper has excellent driving character.

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).

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