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

Number: pap. 3421

Author(s) : ZENG T., BROOKS J., BAROOAH P.

Summary

We propose a method that simultaneously identifies a dynamic model of a building’s temperature in the presence of large, unmeasured disturbances, and a transformed version of the unmeasured disturbance. Our method uses `1-regularization to encourage the identified disturbance to be approximately sparse, which is motivated by the piecewise constant nature of occupancy that determines the disturbance. We test our method using both open-loop and closedloop simulation data. Results show that the identified model can accurately identify the transfer functions in both scenarios, even in the presence of large disturbances, and even when the disturbance does not satisfy the piecewise constant property.

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Pages: 10

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Details

  • Original title: Simultaneous identification of linear building dynamic model and disturbance using sparsity-promoting optimization.
  • Record ID : 30024887
  • Languages: English
  • Subject: Environment
  • Source: 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
  • Publication date: 2018/07/09

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