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Optimal Self-Tuning PID Controller Based on Low Power Consumption for a Server Fan Cooling System

机译:基于低功耗的服务器风扇冷却系统最优自调节PID控制器

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摘要

Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server’s fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption.
机译:近来,由于对高密度服务器的需求增加,通过控制风扇速度来节省服务器中的冷却功率已经引起了相当大的关注。本文提出了一种最佳自整定比例积分微分(PID)控制器,该控制器将PID神经网络(PIDNN)与基于风扇功率的优化在时域内的瞬态温度响应中相结合,用于服务器风扇冷却系统。由于冷却系统的热模型是非线性且复杂的,因此构建了一个模拟1U机架服务器的服务器样机系统,并使用三阶非线性曲线拟合创建了一个风扇功率模型,以通过风扇速度控制来确定冷却功率消耗。 。具有时域标准的PIDNN用于调整所有在线和优化的PID增益。当服务器从低功率状态运行到高功率状态时,通过阶跃响应实验对提出的控制器进行了验证。结果表明,如果风扇控制允许电子组件中的轻微温度响应过冲,则可以节省多达14%的服务器风扇冷却功率,这可以为调整PID控制器以控制服务器风扇提供节省时间的策略。低风扇功耗时的最大速度。

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