Torque ripple reduction of switched reluctance motor using fuzzy control

2016 ◽  
Vol 33 (6) ◽  
pp. 1668-1679 ◽  
Author(s):  
Ming-Shyan Wang ◽  
Seng-Chi Chen ◽  
Wei-Chin Fang ◽  
Po-Hsiang Chuang
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Pulse Width Modulation ◽  
Switched Reluctance Motor ◽  
Torque Ripple ◽  
Motor Speed ◽  
Content Type ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Future Work

Purpose – Extensive efforts have been conducted on the improvement of torque ripple in switched reluctance motor (SRM) drive. The purpose of this paper is to estimate initial on time of pulse-width modulation (PWM) and turn-off angle using the motor speed and rotor angle by fuzzy logic. Design/methodology/approach – A fuzzy logic control together with the PWM technique and turn-off angle are used to improve torque ripple and dynamic response. Findings – After determining initial on time of PWM, the rise slope of phase current is increased. Research limitations/implications – Future work will consider to increase the complex of the fuzzy control to adaptively tune parameters and achieve excellent results. Practical implications – The experimental results of the proposed method are presented to show the effectiveness. Originality/value – This paper achieves SRM control by one special PWM technique which is seldom studied.

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).

The Designment and Implenment of Fuzzy Hybrid Pid in Srm Appleller to Electric Valve

2013 ◽  
Vol 367 ◽  
pp. 405-410
Author(s):  
Guo Qing Li ◽  
Dean Zhao ◽  
Hui Jiang
Keyword(s):  
Fuzzy Control ◽  
Strong Coupling ◽  
Pid Control ◽  
Control Method ◽  
Switched Reluctance Motor ◽  
Feedback System ◽  
Switched Reluctance Motors ◽  
Switched Reluctance ◽  
The Core ◽  
Reluctance Motor

To solve the strong coupling and nonlinear of switched reluctance motor (SRM) used in the Electric valve ,we use a fuzzy compound PID control method, and apply it to the switched reluctance motors speed control system.The simulation applys that this method combines the advantages of fuzzy control and PID control and is well applied to non-linears object.Based on the theory, we design the core to the outer loops speed feedback and inner current loops feedback system in TMS320F28335,and describe the specific hardware and software structure, morely verify the feasibilitys test. The theory can solve the problem that the traditional PID cannot meet the variation of the parameter from the electric valve.

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.

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