2020
DOI: 10.1007/s43236-020-00112-9
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Evolutionary algorithm based selective harmonic elimination for three-phase cascaded H-bridge multilevel inverters with optimized input sources

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Cited by 11 publications
(4 citation statements)
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“…Inspired by the configuration of chemical compounds and reactions in the production of new materials [85] Political Optimizer (PO) Inspired by the mathematical mapping of the multistage process of politics [86] Peafowl Optimization Algorithm (POA) Inspired by the group foraging behavior of the peafowl swarm [87] Parasitism-Predation algorithm (PPA) Inspired by the multi-interactions between cuckoos, crows, and cats [88] Smell Agent Optimization (SAO) Inspired by the relationship between a smell agent and an object that vaporizes a small molecule [89] Sperm Swarm Optimization (SSO) Inspired by sperm-ovum interactions in the fertilization procedure [90] Wild Horse Optimizer (WHO) Inspired by the social life behavior of wild horses [91] When the literature was reviewed, no study was found to determine the A and B coefficients in the fitness function given in (10). In many studies, the A and B coefficients are taken as 100 and 50, respectively [56][57][58]61,63,[66][67][68][69]74]. In some studies, only the right part of Equation ( 10) is included in the calculation as a fitness function [59,64,65].…”
Section: Optimization Methods Inspirermentioning
confidence: 99%
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“…Inspired by the configuration of chemical compounds and reactions in the production of new materials [85] Political Optimizer (PO) Inspired by the mathematical mapping of the multistage process of politics [86] Peafowl Optimization Algorithm (POA) Inspired by the group foraging behavior of the peafowl swarm [87] Parasitism-Predation algorithm (PPA) Inspired by the multi-interactions between cuckoos, crows, and cats [88] Smell Agent Optimization (SAO) Inspired by the relationship between a smell agent and an object that vaporizes a small molecule [89] Sperm Swarm Optimization (SSO) Inspired by sperm-ovum interactions in the fertilization procedure [90] Wild Horse Optimizer (WHO) Inspired by the social life behavior of wild horses [91] When the literature was reviewed, no study was found to determine the A and B coefficients in the fitness function given in (10). In many studies, the A and B coefficients are taken as 100 and 50, respectively [56][57][58]61,63,[66][67][68][69]74]. In some studies, only the right part of Equation ( 10) is included in the calculation as a fitness function [59,64,65].…”
Section: Optimization Methods Inspirermentioning
confidence: 99%
“…The validity of the proposed method is tested with GA. The study, in which the heterogeneous comprehensive learning particle swarm optimization (HCLPSO) method is used to find the optimum switching angles in classical 3-phase H-bridge eleven-level multilevel inverters, is given in [68]. The success of the HCLPSO is compared with the gravitational search algorithm (GSA) and differential search algorithm (DSA) methods.…”
Section: Introductionmentioning
confidence: 99%
“…This research paper compares three, five and thirteen level MLIs using the Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) switching technique. SHE-PWM is a modulation technique that switches at low frequency and provides tailored control of low-order harmonics and reduces switching losses [24], [25], [26], [27], [28]. In each case, MLIs will use SHE-PWM control scheme and the output voltage waveform of each has six notch angles (using quarter waveform symmetry).…”
Section: Introductionmentioning
confidence: 99%
“…More recently, a comparative study between different optimization techniques to find precise switching angles for SHE modulation was made by Kundu et al (2018). The GA was used by Iqbal et al (2019) to solve the SHE optimization problem for a seven-level packed U-cell inverter and Kumar et al (2020) applied a Gravitational Search Algorithm and a Learning PSO to obtain optimized switching angles for seven and eleven level inverters.…”
Section: Introductionmentioning
confidence: 99%