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DC-link voltage control of three-phase PWM rectifier by using artificial bee colony based type-2 fuzzy neural network

机译:三相PWM整流器使用人工蜂菌落基于2型模糊神经网络的直流 - 链路电压控制

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摘要

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.
机译:由于半导体开关的结构,脉冲宽度调制(PWM)整流器是非线性系统。因此,这些整流器从AC电源汲取扭曲的电流。已经提出了许多不同的改进来克服PWM整流器引起的问题。在本文中,通过使用A型模糊神经网络(T2FNN)控制器来调节三相PWM整流器的DC-Link电压,该控制器通过使用人造蜜蜂菌落(ABC)优化方法优化参数。通过ABC优化方法优化了T2FNN的前一种和随后的T2FNN的参数。通过基于MATLAB的仿真模型在不同的操作条件下分析ABC-T2FNN控制器的性能。操作条件被认为是恒定的输入,设定点,步骤直流负载变化,不平衡的交流电源和再生模式。通过与经典T2FNN的结果进行比较,通过比较来验证从所提出的控制器获得的模拟结果。当研究了PWM整流器的结果时,可以看出,基于所提出的控制器的PWM整流器比传统的T2FNN控制器的所有操作条件具有更好的动态响应。

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