Parameter Identification of Single-Phase Inverter Based on Improved Moth Flame Optimization Algorithm. Issue 4 (16th March 2019)

• Record Type: Journal Article
• Authors: Wu, Zhongqiang; Shen, Dandan; Shang, Mengyao; Qi, Songqi
• Is Part Of: Electric power components and systems. Volume 47:Issue 4/5(2019)
• Page Start: 456
• Page End: 469
• Publication Date: 2019-03-16
• Subjects: parameter identification -- fault diagnosis -- optimization algorithm -- single-phase inverter -- transfer function model -- moth flame optimization algorithm -- particle swarm optimization -- genetic algorithm -- Fast Fourier transform -- Levy flight; Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2019.1607922
• Languages: English
• ISSNs: 1532-5008

Abstract

Abstract: 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.