首页> 外文会议>Annual Meeting of the North American Fuzzy Information Processing Society >Study of Two Control Strategies Based in Fuzzy Logic and Artificial Neural Network Compared with an Optimal Control Strategy Applied to a Buck Converter
【24h】

Study of Two Control Strategies Based in Fuzzy Logic and Artificial Neural Network Compared with an Optimal Control Strategy Applied to a Buck Converter

机译:基于模糊逻辑和人工神经网络的两种控制策略与应用于降压转换器的最优控制策略

获取原文

摘要

The dc-dc converters are highly efficient tools used to supply power to different systems, they have a nonlinear behavior and variations at their main parameters could affect their stability. This document studies and compares different control strategies, linear and non linear controllers applied to a Buck converter. There are mainly three control strategies treated in this paper. First an optimal control based design, by employing The Quadratic Performance Index (QPI) is used, second a knowledge based fuzzy control is studied and third an Artificial Neural Network (ANN) as a dynamic emulator of the fuzzy control is proposed. Some comparisons about the systems composed by the plant and a controller, in variation of a few plant parameters were made; in addition the computational time in simulation is compared between the two intelligent controllers.
机译:DC-DC转换器是高效的工具,用于向不同系统提供电源,它们具有非线性行为,主要参数的变化可能影响其稳定性。本文档研究并比较了应用于降压转换器的不同控制策略,线性和非线性控制器。本文主要有三种控制策略。首先使用基于最佳控制的设计,通过采用二次性能指标(QPI),研究了基于知识的模糊控制,并提出了一种作为模糊控制的动态仿真器的第三个人工神经网络(ANN)。对植物和控制器组成的系统的一些比较,在几个植物参数的变化中进行了一些比较;此外,在两个智能控制器之间比较模拟的计算时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号