摘要
基于双闭环控制的BUCK-Boost矩阵变换器(BBMC)具有优良的电气性能,然而其控制参数因采用试凑法获得而难以达到最佳控制效果,为此提出采用微粒群算法对其控制参数进行优化。介绍了BBMC双闭环控制策略与微粒群算法的基本原理,阐述了采用微粒群算法对BBMC双闭环控制策略的控制参数进行优化的具体设计方法,并利用MATLAB对其控制效果进行了仿真验证,同时与试凑法获得的控制参数进行了对比仿真分析。结果表明:利用微粒群算法优化获得的控制参数较试凑法获得的控制参数具有更好的控制效果,BBMC输出波形的谐波失真度更小。
BUCK-Boost matrix converter （ BBMC ） which is controlled by double-loop control strategy has excellent electric properties. Its best control effect is difficult to achieve, because its control parameters are obtained by experiment method. So the particle swarm optimization （ PSO ） is adopted tooptimize its control parameters. In this paper, the basisof PSOand that of double-loop control strategy of BBMC are explained, and the method of optimizingits control parameters by PSO is elaborated. At the end of this paper, the effect of this control strategyis tested by MATLAB and compared with that obtain by experiment method. The resultsindicate that the control parameters obtained by PSO have better effect and lesserharmonic distortion of output waveform.
出处
《电气自动化》
2015年第1期27-30,共4页
Electrical Automation
基金
国家自然科学基金(51477047)
湖南省科技重大专项项目(2014FJ1004)
湖南省教育厅优秀青年科研项目(12B043)
