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Comparative Study of a Fuzzy Logic Based Controller and a Neuro-Fuzzy logic Based Controller for Computer Fan

机译:基于模糊逻辑的控制器与基于神经模糊逻辑的计算机风扇控制器的比较研究

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The impact of soft-computing in modern day engineering and technology cannot be overemphasized. Fuzzy logic approach as proposed by Lofti Asker Zadeh, popularized by the Japanese, has found its way into the control of many domestic and industrial appliances/machines. Unlike the popular PID controllers and the pulse width modulation based controllers, the performance of computer fan is investigated using the fuzzy logic approach with two inputs parameters, that is, the computer loads and the temperature and one output parameter which is the speed at which the computer fan operates. For the fuzzy inference system, four membership functions are selected for the inputs as well as the output. Relevant rules are set to determine the operating conditions and boundaries for the controller. In order to make the controller adaptive, neurofuzzy logic appproach is used with parameters set as the case with fuzzy logic. Training of the controller is carried out and the performance of each controller is presented in three dimensional view and two dimensional surface view with neurofuzzy based controller, in performance, having an edge over the fuzzy logic based controller. Keywords: Anfis, Fuzzy logic, Computer fan, Controller, Performance comparison
机译:不能过分强调软计算在现代工程技术中的影响。由日本人普及的Lofti Asker Zadeh提出的模糊逻辑方法已经进入许多家用和工业设备/机器的控制中。与流行的PID控制器和基于脉宽调制的控制器不同,使用模糊逻辑方法研究计算机风扇的性能,该方法具有两个输入参数,即计算机负载,温度和一个输出参数,即转速。电脑风扇运转。对于模糊推理系统,为输入和输出选择四个隶属函数。设置相关规则以确定控制器的操作条件和边界。为了使控制器具有自适应性,将神经模糊逻辑方法与参数(如模糊逻辑的情况下)一起使用。进行控制器的训练,并使用基于神经模糊的控制器在三维视图和二维表面视图中呈现每个控制器的性能,并且在性能上优于基于模糊逻辑的控制器。关键字:Anfis,模糊逻辑,计算机风扇,控制器,性能比较

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