Simultaneous identification of linear building dynamic model and disturbance using sparsity-promoting optimization

Simultaneous identification of linear building dynamic model and disturbance using sparsity-promoting optimization
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使用稀疏性促进优化同时识别线性建筑动力模型和扰动

DOI:
10.1016/j.automatica.2021.109631
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发表时间:
2021
期刊:
影响因子:
6.4
通讯作者:
Barooah, Prabir
Barooah, Prabir
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zeng, Tingting;Brooks, Jonathan;Barooah, Prabir

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我们提出了一种方法,可以同时识别建筑物温度动力学的面向控制模型和影响建筑物的未测量扰动的转换版本。我们的方法使用1-正则化来鼓励识别的干扰近似稀疏,这是由决定干扰的占用率的缓慢变化性质引起的。该方法涉及求解一个可行的凸优化问题,以保证所识别的黑箱模型(线性定常系统)具有被控对象的已知特性,特别是输入输出稳定性和正直流增益。这些特点使人们能够使用该方法作为自我学习控制系统的一部分,在该系统中,建筑物的模型会定期更新,而不需要人工干预。给出了该方法在模拟和实际建筑数据上的应用结果。
We propose a method that simultaneously identifies a control-oriented model of a building’s temperature dynamics and a transformed version of the unmeasured disturbance affecting the building. Our method uses ℓ 1-regularization to encourage the identified disturbance to be approximately sparse, which is motivated by the slowly-varying nature of occupancy that determines the disturbance. The proposed method involves solving a feasible convex optimization problem that guarantees that the identified black-box model, a linear time-invariant system, possesses known properties of the plant, especially input–output stability and positive DC gains. These features enable one to use the method as part of a self-learning control system in which the model of the building is updated periodically without requiring human intervention. Results from the application of the method on data from a simulated and real building are provided.
DOI: 10.1109/tcst.2019.2949546
发表时间: 2020-09
影响因子: 4.8
作者:
Tingting Zeng;P. Barooah
通讯作者: Tingting Zeng;P. Barooah
用于建筑 HVAC 系统节能控制的自主 MPC 方案
DOI: 10.23919/acc45564.2020.9147753
发表时间: 2020
期刊: 2020 American Control Conference (ACC
影响因子: --
作者:
Zeng, Tingting;Barooah, Prabir
通讯作者: Barooah, Prabir
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者:
Donghun Kim;Jie Cai;J. Braun;Kartik B. Ariyur
通讯作者: Kartik B. Ariyur
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者:
Tingting Zeng;J. Brooks;P. Barooah
通讯作者: P. Barooah
DOI: 10.1016/j.buildenv.2017.10.020
发表时间: 2018-01-15
影响因子: 7.4
作者:
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通讯作者: Barooah, Prabir