Risk-based online robust optimal control of air-conditioning systems for buildings requiring strict humidity control considering measurement uncertainties

Chaoqun Zhuang, Shengwei Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


The total floor area and energy consumption of buildings or spaces requiring strict temperature and humidity control have been growing rapidly worldwide. A major challenge for achieving energy-efficient control of air-conditioning systems in such applications is the measurement uncertainties underlying the systems’ online optimal control decisions under ever-changing working conditions. This paper proposes a risk-based online robust optimal control strategy for multi-zone air-conditioning systems considering component performance degradation and measurement uncertainties. A risk-based online control decision scheme, as the core of the strategy, is developed for decision-making by compromising the failure risks and energy benefits of different control modes considering uncertainties in the information used. The proposed strategy is tested and implemented in a simulation platform based on an existing pharmaceutical industrial building. The results show that the proposed strategy made the optimal online control decisions, allowing for the measurement uncertainties. Compared with a commonly used control strategy, the proposed strategy achieved approximately 20% overall energy saving in the test period.

Original languageEnglish
Article number114451
JournalApplied Energy
Publication statusPublished - 1 Mar 2020


  • Air-conditioning
  • Cleanroom
  • Measurement uncertainty
  • Online optimal control
  • Risk-based control

ASJC Scopus subject areas

  • Building and Construction
  • Energy(all)
  • Mechanical Engineering
  • Management, Monitoring, Policy and Law

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