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首页> 外文期刊>Electric Power Components and Systems >Parameter Identification of Single-Phase Inverter Based on Improved Moth Flame Optimization Algorithm
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Parameter Identification of Single-Phase Inverter Based on Improved Moth Flame Optimization Algorithm

机译：基于改进型飞蛾火焰优化算法的单相逆变器参数辨识

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摘要

By identifying the parameters of electronic circuit, parametric fault diagnosis of power electronic circuits can be realized. Many intelligent optimization algorithms are used to identify the parameters of electronic circuit, but most of them have the defects of slow convergence rate and easy to fall into local minimum. Moth flame optimization algorithm is a novel swarm intelligence bionic algorithm based on the intelligence behavior of moth positioning, which also has the above drawbacks. In order to improve the performance of algorithm, when updating the moth position, moth firstly moves in a straight line to the optimal position, then Levy flight is added. The improved algorithm improves the global optimization ability and accelerates the convergence speed. The improved moth flame optimization algorithm is applied for the parameter identification of single-phase inverter. The identification result is compared with the results of the other optimization techniques. The effectiveness and superiority of the improved algorithm are verified.
机译：通过识别电子电路的参数，可以实现电力电子电路的参数故障诊断。许多智能优化算法被用来识别电子电路的参数，但是它们大多数都具有收敛速度慢且易于陷入局部最小值的缺点。飞蛾火焰优化算法是一种基于飞蛾定位智能行为的新型群体智能仿生算法，也具有上述缺点。为了提高算法的性能，在更新飞蛾位置时，飞蛾首先沿直线移动到最佳位置，然后再增加Levy飞行。改进后的算法提高了全局优化能力，加快了收敛速度。将改进的飞蛾火焰优化算法应用于单相逆变器的参数辨识。将识别结果与其他优化技术的结果进行比较。验证了改进算法的有效性和优越性。

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