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Adaptive Predictive Control of a data center cooling unit

机译:数据中心冷却单元的自适应预测控制

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摘要

As server densities increase to support the rising demand for high density computing, traditional room cooling infrastructure is struggling to keep up. Rack-mounted cooling units are increasingly being deployed in data centers. These cooling units are located closer to the heat sources (the servers) which allow them to cool more efficiently than traditional cooling infrastructure. In this work, a Multi-Input Single-Output (MISO) Adaptive Predictive Controller (APC) for rack-mounted cooling units is investigated and implemented using a low-cost general-purpose microcontroller. The proposed APC is implemented using Weighted Recursive Least Squares (WRLS) and a sub-optimal but fast algorithm based on the General Predictive Controller (GPC) approach.These are combined with a variable forgetting factor and variable prediction horizon algorithms. In addition,methods are proposed to handle stability issues arising due to practical hardware limitations. The controller is implemented on a real single rack system and challenges for practical implementation are addressed and illustrated. The proposed APC is also compared (via simulation) to a standard APC with equivalent complexity and a split-range PI controller. The results show that the proposed controller outperforms both the standard APC and the split-range PI controllers with respect to Mean Squared Error (MSE).
机译:随着服务器密度的增加,支持高密度计算的不断增长,传统的房间冷却基础设施正在努力跟上。架起的冷却单元越来越多地部署在数据中心中。这些冷却单元更靠近热源(服务器),其允许它们比传统的冷却基础设施更有效地冷却。在这项工作中,使用低成本的通用微控制器来研究和实现用于机架式冷却单元的多输入单输出(MISO)自适应预测控制器(APC)。所提出的APC使用加权递归最小二乘(WRL)和基于一般预测控制器(GPC)方法的子最优但快速算法来实现。这些与可变遗忘因子和可变预测地平线算法组合。此外,提出了方法以处理由于实际硬件限制而产生的稳定性问题。控制器在真正的单一机架系统上实现,并解决了实际实现的挑战。所提出的APC也将(通过模拟)与具有等效复杂度和分流PI控制器的标准APC进行比较。结果表明,所提出的控制器占据了标准APC和分流PI控制器的差异相对于均方误差(MSE)。

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