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Design of an Artificial Neural Network Controller for a Tankless Water Heater By Using a Low-Profile Embedded System

机译:使用低调嵌入式系统设计无油桶水加热器的人工神经网络控制器

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Tankless water heaters (TWHs) have been become more popular day-by-day in special because of the low-power consumption that characterizes these devices in comparison with the tank water heaters. Nonetheless, it is desirable that these systems have a rapid response to disturbances such as changes in water flow or the inlet temperature. Different methods of classic control have been used for solving this problem for decades. These techniques provide a good solution although not necessarily the optimal one. With the recent boom in automatic control techniques based on Artificial Neural Networks (ANNs) [1]-[3] and the scaling in terms of computational power of embedded systems, this has led to the use of ANNs in low-profile embedded systems. In this work, we present an implementation of an ANN for a commercial application of a TWH running on a low-profile embedded system where we demonstrated that the stabilization time is reduced by up to 25% whilst the overshoot by up to 50%, both in comparison with a classic methods of automatic control using a low-performance microcontroller.
机译:由于低功耗与油箱水加热器相比,无水加热器(TWHS)一直变得更加受欢迎的日常白天的特殊日子。尽管如此,希望这些系统对扰动的快速响应,例如水流或入口温度的变化。几十年来,已经使用了不同的经典控制方法来解决这个问题。这些技术提供了良好的解决方案,尽管不一定是最佳的解决方案。随着最近基于人工神经网络(ANNS)[1] - [3]的自动控制技术的繁荣,并且在嵌入式系统的计算能力方面的缩放,这导致了在低调嵌入式系统中的ANN。在这项工作中,我们展示了一个ANN的实施,用于在低调嵌入式系统上运行的TWH的商业应用,我们证明稳定时间减少了最多25 %,而过冲最多可达50 % ,与使用低性能微控制器的自动控制方法相比。

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