基于遗传算法的异步电动机功率因数自寻优控制  

Control of Self-optimization of Asynchronous Motor Power Factor Based on Genetic Algorithms

作　　者：杨斌[1] 刘惠康[1] 林森[1] 

机构地区：[1]武汉科技大学信息科学与工程学院,湖北武汉430081

出　　处：《大电机技术》2007年第3期23-26,共4页Large Electric Machine and Hydraulic Turbine

摘　　要：遗传算法是一种模拟自然进化过程的简单、高效的优化组合方法。本文提出运用遗传算法来解决异步电动机在轻载和空载时功率因数低下的问题,并在理论上对功率因数优化的可能性进行了证明。实验和仿真结果都表明了这种基于遗传算法的异步电动机功率因数的自寻优控制,方法简单、有效,具有极高的工程应用价值。Genetic algorithms are easy and efficient methods of optimization and combination by simulating the natural evolution course. This paper puts forward an idea of using genetic algorithms to solve the problem of low power factor at no load and light load with asynchronous motor and the possibility of power factor optimization is testified in theory. Result of experiments and simulations shows that the control of self-optimization of asynchronous motor power-factor based on genetic algorithms is an efficient method and has extremely high application values.

关 键 词：遗传算法 功率因数优化 自寻优控制 异步电动机 

分 类 号：TM343[电气工程—电机]