Comparative Analysis of PWM AC Choppers with Different Loads with and Without Neural Network Application

None Mariem Bounabi, None Guma Ali
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Abstract

In this paper, we focus on the "Artificial Neural Network (ANN) based PWM-AC chopper". This system is based on the PWM AC chopper-encouraged single-phase induction motor. The main purpose of this paper is to design and implement an ideal technique regarding speed control. Here analyzed PWM-based AC-AC converter with resistive load, R-L load and finally, the PWM AC chopper is fed to single phase induction for speed control. Using other soft computing and optimization techniques such as Artificial Neural Networks, Fuzzy Logic, Convolution algorithm, PSO, and Neuro Fuzzy can control the Speed. We used Artificial Neural Network to control the Speed of the PWM-AC Single phase induction motor drive. The Neural Network toolbox has been further used for getting desired responses. Neural system computer programs are executed in MATLAB. The performance of the proposed method of ANN system of PWM AC Chopper fed single phase induction motor drive is better than other traditional and base methods for controlling the Speed, based on the MOSFET.
应用与未应用神经网络时不同负载PWM交流斩波器的比较分析
本文主要研究“基于人工神经网络的PWM-AC斩波器”。该系统基于PWM交流斩波激励单相感应电动机。本文的主要目的是设计和实现一种理想的速度控制技术。本文分析了电阻负载、R-L负载下基于PWM的交流-交流变换器,最后将PWM交流斩波馈入单相感应进行速度控制。使用其他软计算和优化技术,如人工神经网络、模糊逻辑、卷积算法、粒子群算法和神经模糊算法可以控制速度。采用人工神经网络控制PWM-AC单相感应电动机的转速。神经网络工具箱已被进一步用于获得期望的响应。神经系统计算机程序在MATLAB中执行。本文提出的基于MOSFET的PWM交流斩波馈电单相感应电机驱动人工神经网络系统的性能优于其他传统和基本的速度控制方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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