基于遗传学习人工蜂群算法的级联多电平逆变器SHEPWM研究

Research on SHEPWM of Cascaded Multilevel Inverters Based on Artificial Bee Colony Algorithm Based on Genetic Learning

针对多电平逆变器的特定谐波消除脉冲宽度调制(SHEPWM)问题,引入遗传学习(GL)算法对人工蜂群算法(ABC)进行改进,避免传统人工蜂群算法易陷入局部最优、运算迭代速度慢和优化精度较差等问题,达到了优化开关角的目的。仿真结果表明,改进ABC-GL算法的开关角度值正确有效,消除了特定的谐波分量,提高了计算速度和精度。

Aiming at the specific harmonic elimination pulse width modulation(SHEPWM)problem of multi-level inverters,a genetic learning(GL)algorithm was introduced to improve the artificial bee colony(ABC)algorithm,so as to avoid the traditional artificial bee colony algorithm easily falling into local optimum,problems such as slow operation iteration speed and poor optimization accuracy.The improved ABC-GL algorithm achieved the purpose of optimizing the switching angle.The simulation results show that the switching angle value of the improved ABC-GL algorithm is correct and effective,eliminating specific harmonic components and improving the calculation speed and accuracy.