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Switching-off Angle Control for Switched Reluctance Motor Using Adaptive Neural Fuzzy Inference System
International Journal of Energy and Power Engineering
Volume 4, Issue 1, February 2015, Pages: 39-45
Received: Dec. 5, 2014; Accepted: Dec. 17, 2014; Published: Feb. 6, 2015
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Authors
Liu Zhi Jian, Faculty of Electric Power Engineering, Kunming University of Science and technology, Kunming City, Yunnan Province, China
Nguyen Le Minh Tri, Faculty of Electric Power Engineering, Kunming University of Science and technology, Kunming City, Yunnan Province, China; Faculty of Electrical Engineering, Kien Giang Technology and Economics College, Kien Giang Province, Vietnam
Nguyen Le Thai, Faculty of Electric and Electronic Engineering, Tuy Hoa Industrial College, Tuy Hoa City, Phu Yen Province, Vietnam
Phan Xuan Le, Faculty of Electric Power Engineering, Kunming University of Science and technology, Kunming City, Yunnan Province, China; Faculty of Electric and Electronic Engineering, Tuy Hoa Industrial College, Tuy Hoa City, Phu Yen Province, Vietnam
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Abstract
Switched reluctance motors (SRM) have a wide range of applications in industries due to the special properties of this motor. However, because of its dynamical nonlinearities, so the problems control of SRM is complex. This paper proposed an adaptive intelligent controller for SRM with the aim to improve the ripple of torque. First, we use a fuzzy logic controller to control switch-off angle, and then proposes a new controller by means of Adaptive Neural Fuzzy Inference (ANFIS). Simulation results are given to show the efficacy of the proposed method.
Keywords
SRM, Fuzzy logic, ANFIS
To cite this article
Liu Zhi Jian, Nguyen Le Minh Tri, Nguyen Le Thai, Phan Xuan Le, Switching-off Angle Control for Switched Reluctance Motor Using Adaptive Neural Fuzzy Inference System, International Journal of Energy and Power Engineering. Vol. 4, No. 1, 2015, pp. 39-45. doi: 10.11648/j.ijepe.20150401.16
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