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A novel neural network aided fuzzy logic controller for a variable speed (VS) direct expansion (DX) air conditioning (A/C) system

机译:用于变速(VS)直接膨胀(DX)空调(A / C)系统的新型神经网络辅助模糊逻辑控制器

摘要

A novel artificial neural network (ANN) aided fuzzy logic controller for simultaneous control of indoor air temperature and humidity using a variable speed (VS) direct expansion (DX) air conditioning (A/C) system, through combining the complementary merits of fuzzy logic controllers and ANN modeling was developed and is reported in this paper. A novel control principle was proposed to decouple the temperature and humidity control loops by introducing two interim variables of sensible and latent output cooling capacity of the DX A/C system. A fuzzy logic system was redesigned to simplify both its calculation and structure by using weights of linguistic variables. To enable the ANN model developed to be functional at the normal operational range of indoor air parameters, previously reported inherent operating characteristics of a VS DX A/C system were used for training and testing the ANN models. The novel controller so developed was tested using an experimental VS DX A/C system. Both the command following tests and disturbance rejection tests showed that the air dry-bulb and wet-bulb temperatures were properly controlled by the controller developed with satisfactory control performances in terms of control accuracy and sensitivity.
机译:一种新型的人工神经网络(ANN)辅助模糊逻辑控制器,通过结合模糊逻辑的互补优点,使用变速(VS)直接膨胀(DX)空调(A / C)系统同时控制室内空气温度和湿度开发了控制器和ANN建模,并在本文中进行了报道。提出了一种新颖的控制原理,通过引入DX A / C系统的显性和潜性输出冷却能力的两个临时变量来解耦温度和湿度控制回路。通过使用语言变量的权重,对模糊逻辑系统进行了重新设计,以简化其计算和结构。为了使所开发的ANN模型能够在室内空气参数的正常运行范围内正常运行,以前报道的VS DX A / C系统的固有运行特性用于训练和测试ANN模型。如此开发的新型控制器已通过实验VS DX A / C系统进行了测试。指令跟随测试和干扰抑制测试均表明,干球温度和湿球温度均由开发的控制器进行了适当控制,该控制器在控制精度和灵敏度方面具有令人满意的控制性能。

著录项

  • 作者

    Li Z; Xu X; Deng S; Pan D;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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