期刊
MICROPROCESSORS AND MICROSYSTEMS
卷 78, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.micpro.2020.103250
关键词
Artificial bee colony; Power quality; PWM rectifier; Type-2 fuzzy neural network
The pulse width modulation (PWM) rectifiers are nonlinear systems due to semiconductor switches in their structure. Therefore, these rectifiers draw a distorted current from AC supply. Many different improvements have been proposed to overcome problems caused by PWM rectifiers. In this paper, DC-link voltage of three-phase PWM rectifier is regulated by using a Type-2 Fuzzy Neural Network (T2FNN) controller that parameters are optimized by using Artificial Bee Colony (ABC) optimization method. The parameters in antecedent and consequent parts of T2FNN are optimized by ABC optimization method. The performance of ABC-T2FNN controller is analyzed under different operating conditions through simulation model based on MATLAB. The operating conditions are considered as constant input, set point, a step DC load change, unbalanced AC supply and regenerative mode. The simulation results obtained from the proposed controller are verified by comparing with the results of the classical T2FNN. When the results of PWM rectifiers are investigated, it is seen that PWM rectifier based on the proposed controller has better dynamic response for all operating conditions than conventional T2FNN controller.
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