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
复制标题
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
中科院分区:
文献类型:
--
作者:
Zeng, Tingting;Brooks, Jonathan;Barooah, Prabir
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.
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影响因子:
4.8
作者:
Tingting Zeng;P. Barooah
通讯作者:
Tingting Zeng;P. Barooah
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
影响因子:
7.4
作者:
Coffman, Austin R.;Barooah, Prabir
通讯作者:
Barooah, Prabir