基于群智能的双非对称绕组异步电动机控制器

Amr Amin, M. I. Korfally, A. Sayed, O. Hegazy
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引用次数: 3

摘要

本文采用基于粒子群优化(PSO)的磁场定向方法控制双非对称绕组异步电动机的转速。通过对任意工作点的最优转子磁链的计算,得到电机的最大效率。此外,在保持快速动态响应的同时,电磁转矩也得到了提高。在本研究中,采用了一种新的方法来评估转子的最佳磁链水平。该方法基于粒子群算法(PSO)。粒子群优化算法是群智能算法的一种。本研究提出两种速度控制策略。这些是面向场的控制器(FOC)和基于PSO的FOC。结果表明,基于粒子群算法的FOC比传统的FOC方法更节能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Swarm Intelligence-Based Controller of Two-Asymmetric Windings Induction Motor
In this paper, applying field orientation based on Particle Swarm Optimization (PSO) controls the speed of two-asymmetrical windings induction motor. The maximum efficiency of the motor is obtained by the evaluation of optimal rotor flux at any operating point. In addition, the electro-magnetic torque is also improved while maintaining a fast dynamic response. In this research, a novel approach is used to evaluate the optimal rotor flux level. This approach is based on Particle Swarm Optimization (PSO). PSO method is a member of the wide category of Swarm Intelligence methods (SI). This research presents two speed control strategies. These are field- oriented controller (FOC) and FOC based on PSO.. The results have demonstrated that the FOC based on PSO method saves more energy than the conventional FOC method.
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