Multiobjective Genetic Algorithm to Minimize the THD in Cascaded Multilevel Converters with V/F Control

Induction motor speed control in a DSP-based low-THD multi-level converter

“…With the machine's nominal voltage assignment at 220 Vrms, the nominal frequency 50 Hz, the frequency range will be [45 Hz, 55 Hz] with steps of ∆f=1 Hz, the Vboost level is set at 30 Vrms line. With these data the algorithm was run in Matlab and the activation angles of 11 modulations with low harmonic content and RMS values following the law V vs f were obtained with the previous data [10]. Giving the exact switching angles or state changes of the GPIO pins of the card described for the frequency range pre-set in the genetic algorithm was obtained as a matrix [10] which has switching angles and positions.…”

“…The induction motor is controlled by a V/F law, with modulations obtained by a multi-target genetic algorithm [10], where the obtained modulations are sent to the TMS320F28069M card which is in charge of sending the control signals to the converter semiconductors, acquire data for further processing and control for the three-phase induction machine [11], the overall system is designed to minimize the harmonic content of the input current, to precisely regulate the DC bus [12] the advanced control approach thought for the future [13] - [15].…”

“…The genetic algorithm in equations 1 and 2 described in works [10] and [17] and in accordance with the IEEE 519 standard of 1992 [18], defines the total harmonic distortion calculated up to the 50th harmonic where the h1 harmonic is the fundamental component and h n the peak of the n harmonic:…”

“…Where n takes odd values different from three because the harmonics multiple of 3 are suppressed in the connection of the transformers, that is 5, 7, 11, 13, 17, ... and Li are the components of the vector L= [a b c d] (at level 1, b level 2, c level 3 and level 4); Para, the rms value can be defined[10].…”

Using grey wolf optimizer to minimize voltage total harmonic distortion of a salient-pole synchronous generator

“…However there are limited researches on this subject those are using metaheuristics (especially on swarm intelligence). The related remarkable studies using metaheuristics are focused on using genetic algorithm (GA) [4][5][6][7][8][9][10], particle swarm optimization (PSO) [11][12][13][14][15], clonal selection algorithm (CSA) [16], ant-lion optimizer (ALO) [17], and adaptive mosquito blood search algorithm (AMBS) [18].…”