Stochastic Model Predictive Control for Building Climate Control

F. Oldewurtel, C.N. Jones, A. Parisio, M. Morari

    Research output: Contribution to journalArticlepeer-review

    89 Downloads (Pure)


    In this brief paper, a Stochastic Model Predictive Control formulation tractable for large-scale systems is developed. The proposed formulation combines the use of Affine Disturbance Feedback, a formulation successfully applied in robust control, with a deterministic reformulation of chance constraints. A novel approximation of the resulting stochastic finite horizon optimal control problem targeted at building climate control is introduced to ensure computational tractability. This work provides a systematic approach toward finding a control formulation which is shown to be useful for the application domain of building climate control. The analysis follows two steps: 1) a small-scale example reflecting the basic behavior of a building, but being simple enough for providing insight into the behavior of the considered approaches, is used to choose a suitable formulation; and 2) the chosen formulation is then further analyzed on a large-scale example from the project OptiControl, where people from industry and other research institutions worked together to create building models for realistic controller comparison. The proposed Stochastic Model Predictive Control formulation is compared with a theoretical benchmark and shown to outperform current control practice for buildings.
    Original languageEnglish
    Pages (from-to)1198-1205
    Number of pages7
    JournalI E E E Transactions on Control Systems Technology
    Issue number3
    Early online date1 Aug 2013
    Publication statusPublished - May 2014


    • Affine disturbance feedback (ADF), building climate control, chance constraints, Stochastic model predictive control (SMPC)


    Dive into the research topics of 'Stochastic Model Predictive Control for Building Climate Control'. Together they form a unique fingerprint.

    Cite this