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The Implementation of Mamdani’s Fuzzy Model for Controlling the Temperature of Chicken Egg Incubator

机译:Mamdani模糊模型控制鸡蛋孵化器温度的实现

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Today, development of technology is rapidly growing in many fields, including in animal husbandry. This technology could be applied in the process of hatching eggs in chicken farms. Since the process of hatching egg was become an important process that correlated with the failure rate in hatching eggs. In order to get an optimal process of hatching eggs, temperature must be controlled as closely as an ideal temperature, which is around 37-40 Celsius. This study builds the prototype of chicken egg incubator system whose temperature was controlled using a Mamdani logic fuzzy control, so it’s can run optimally. We use DFTII sensor to get the temperature and humidity of incubator as an input of fuzzy logic. Using a fuzzy logic to control the temperature, the output of this system is the speed of fan (PWM). Furthermore, we use 2 lamps to make the temperature warmer, so that the temperature of this incubator could be control in an ideal temperature. We do software testing and overall system performance testing. Software testing is carried out to see whether the implemented fuzzy logic is in accordance with the expected, by comparing the results obtained from a system built with manual calculations and simulation calculations. Based on the test results, it is found that the fuzzy system has been implemented successfully with 47.36% success. While the results of the overall system performance test show that the system being built has worked well.
机译:如今,技术发展在包括畜牧业在内的许多领域都在迅速增长。这项技术可用于养鸡场孵化卵的过程中。由于孵化过程已成为与孵化失败率相关的重要过程。为了获得最佳的孵化过程,必须将温度控制在理想温度附近,理想温度大约为37至40摄氏度。这项研究建立了鸡蛋孵化器系统的原型,该系统使用Mamdani逻辑模糊控制来控制温度,因此可以最佳运行。我们使用DFTII传感器获取培养箱的温度和湿度作为模糊逻辑的输入。使用模糊逻辑控制温度,该系统的输出为风扇速度(PWM)。此外,我们使用2盏灯使温度升高,以便可以将培养箱的温度控制在理想温度下。我们进行软件测试和整体系统性能测试。通过比较从使用人工计算和仿真计算构建的系统中获得的结果,进行软件测试,以查看所实现的模糊逻辑是否符合预期。根据测试结果,发现模糊系统已成功实施,成功率为47.36%。总体系统性能测试的结果表明,所构建的系统运行良好。

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