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Model-based predictive control for buildings with decoupling and reduced-order modeling.

Number: pap. 3404

Author(s) : KIM D., BRAUN J. E.

Summary

The computational cost of applying model-based predictive control (MPC) grows significantly with increasing complexity of the system causing issues in the real-time implementation and feasibility of MPC. The objective of the study is to develop an efficient method to implement MPC in order to overcome the feasibility issues for multizone buildings where there are significant degrees of freedom with respect to optimizing HVAC system supervisory control variables and multi-zone air temperatures set points. A method which decouples the plant and building analyses is investigated based on the fact that the plant dynamics occur on a relatively small time scale compared to the dynamics of the building. Also, a state-space transformation-based technique is applied to determine a reducedorder model that is more amenable to control optimization. Results are presented for some case studies using a simulation test bed.

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Pages: 10 p.

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Details

  • Original title: Model-based predictive control for buildings with decoupling and reduced-order modeling.
  • Record ID : 30006804
  • Languages: English
  • Source: 2012 Purdue Conferences. 2nd International High Performance Buildings Conference at Purdue.
  • Publication date: 2012/07/16

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