Performance of 4 phase SRM for various controllers and optimized using genetic algorithm

S. Poorani
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引用次数: 1

Abstract

This paper presents the idea of using the Switched Reluctance Motor (SRM) as an alternative to previously used drives, in wide good and other industrial applications. In order to show the advantage of the SRM, the speed control of a switched reluctance motor (SRM) is designed by blending two artificial intelligence techniques, genetic algorithms and fuzzy PI control. Here the Genetic Algorithm (GA) is used to optimize the rules of fuzzy inference system. The importance of the fuzzy PI controller is highlighted by comparing the performance of various control approaches, including PI control and fuzzy control for speed control of SRM motor drive in terms of rise time, settling time, overshoot and it is optimized using GA.
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采用遗传算法优化了四相SRM控制器的性能
本文提出的想法,使用开关磁阻电机(SRM)作为替代以前使用的驱动器,在广泛的良好和其他工业应用。为了充分发挥开关磁阻电机的优势,将遗传算法和模糊PI控制两种人工智能技术相结合,设计了开关磁阻电机的速度控制。本文采用遗传算法对模糊推理系统的规则进行优化。通过比较各种控制方法的性能,突出了模糊PI控制器的重要性,包括PI控制和模糊控制在SRM电机驱动速度控制中的上升时间、稳定时间、超调量,并使用遗传算法对其进行优化。
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