2022
DOI: 10.1016/j.apenergy.2021.118297
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Tube-based robust model predictive control of multi-zone demand-controlled ventilation systems for energy saving and indoor air quality

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Cited by 29 publications
(7 citation statements)
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“…This could save 15.1–20.7 % of electricity usage while providing a better indoor environment. Li et al [36] proposed a data-driven MPC strategy to optimize the energy efficiency and indoor air quality of multizone demand-controlled ventilation systems, which could handle the issue of uncertainties in a real duct network system. Their experimental results showed a reduction in IAQ cost by 38 % and energy consumption by 30 %.…”
Section: Introductionmentioning
confidence: 99%
“…This could save 15.1–20.7 % of electricity usage while providing a better indoor environment. Li et al [36] proposed a data-driven MPC strategy to optimize the energy efficiency and indoor air quality of multizone demand-controlled ventilation systems, which could handle the issue of uncertainties in a real duct network system. Their experimental results showed a reduction in IAQ cost by 38 % and energy consumption by 30 %.…”
Section: Introductionmentioning
confidence: 99%
“…Because robust model predictive control (RMPC) [20][21][22] contains the merits of robust control and MPC, the problem of poor performance caused by model uncertainty can be well improved. Research on RMPC is gaining increasing interest.…”
Section: Introductionmentioning
confidence: 99%
“…A vivid example is that when the whole family gathers in the living room throughout the holiday, a large amount of fresh air is still delivered to unoccupied bedrooms and then wastefully exhausted. Even though workable solutions like multi-zone demand control ventilation are readily available and applied in commercial buildings [ [19] , [20] , [21] ], they are less practically implemented in budget-driven residential projects due to their cost and control complexity.…”
Section: Introductionmentioning
confidence: 99%