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蚁群优化算法在发电机励磁控制中的应用研究
引用本文:王德意,袁妮,邱锦东.蚁群优化算法在发电机励磁控制中的应用研究[J].西安理工大学学报,2006,22(2):146-149.
作者姓名:王德意  袁妮  邱锦东
作者单位:西安理工大学,水利水电学院,陕西,西安,710048
摘    要:针对现有发电机励磁控制器参数优化中存在的寻优时间长、易陷入局部最优的问题,提出了一种引入杂交及变异算子的蚁群算法。该算法利用蚁群算法良好的全局寻优能力,避免搜索陷入局部最优,同时借鉴遗传算法的思想,利用杂交及变异算子来进行局部寻优,使其能快速搜索到全局最优点。MATLAB仿真结果表明,该算法可行且有效。

关 键 词:励磁控制  蚁群算法  PID控制  杂交及变异算子  全局最优点
文章编号:1006-4710(2006)02-0146-04
收稿时间:2005-12-12
修稿时间:2005年12月12

An Applied Research on Excitation Control of Synchronous Generator Using Ant Colony Optimization Algorithm
WANG De-yi,YUAN Ni,QIU Jin-dong.An Applied Research on Excitation Control of Synchronous Generator Using Ant Colony Optimization Algorithm[J].Journal of Xi'an University of Technology,2006,22(2):146-149.
Authors:WANG De-yi  YUAN Ni  QIU Jin-dong
Abstract:Aimed at the deficiency in optimization on Excitation Control of Synchronous Generator about long time in optimizing and falling in local best problem easily,a new method based on ant colony algorithm with crossover and mutation operators is presented in this paper.The ability of searching for better global optimization is used to avoid the local best.Meanwhile,the idea of genetic algorithm in using crossover and mutation operators to search for local best is also used to improve the speed of searching for global optimization point.Finally,the simulation results show that the proposed algorithm is effective.
Keywords:excitation control  ant colony algorithm  PID control  crossover and mutation operators  global optimization point
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