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Predictive control oriented subspace identification based on building energy simulation tools

机译:基于建筑节能模拟工具的面向预测控制的子空间识别

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Even though modern control has emerged in numerous control applications, a building automation is still a field where the position of the classical control is almost exclusive. The main reason is that for the synthesis of a predictive controller a decent model for control is needed. In the field of building climate control, it is still problem to obtain a model of large building in an explicit form suitable for control. Most of the approaches either use building modeling software to get detailed model, which is unfortunately in implicit form; or the model is built-up as a first principle model, which usually ends-up as an extreme simplification of the reality. In this paper, a building model identification procedure is presented, wherein the building model is built-up as a first-principle model using a simulation software (detailed, precise, however in implicit form), and then a state-space model is identified by means of subspace identification methods. The main focus of the paper lays on a case study of a large office building, and the entire process of its identification.
机译:尽管现代控制已出现在众多控制应用中,但楼宇自动化仍然是经典控制的位置几乎排他的领域。主要原因是为了综合预测控制器,需要一个合适的控制模型。在建筑物气候控制领域中,仍然存在以适合控制的显式形式获得大型建筑物模型的问题。大多数方法要么使用建筑建模软件来获取详细的模型,遗憾的是隐式形式。或将模型建立为第一原理模型,通常将其最终简化为现实。在本文中,提出了一种建筑模型识别程序,其中使用模拟软件(详细,精确,但采用隐式形式)将建筑模型构建为第一原理模型,然后识别状态空间模型。通过子空间识别方法。本文的主要重点在于对一栋大型办公楼的案例研究,以及其识别的整个过程。

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