A robust model predictive control strategy for improving the control performance of air-conditioning systems

Gongsheng Huang, Shengwei Wang, Xinhua Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

62 Citations (Scopus)


This paper presents a robust model predictive control strategy for improving the supply air temperature control of air-handling units by dealing with the associated uncertainties and constraints directly. This strategy uses a first-order plus time-delay model with uncertain time-delay and system gain to describe air-conditioning process of an air-handling unit usually operating at various weather conditions. The uncertainties of the time-delay and system gain, which imply the nonlinearities and the variable dynamic characteristics, are formulated using an uncertainty polytope. Based on this uncertainty formulation, an offline LMI-based robust model predictive control algorithm is employed to design a robust controller for air-handling units which can guarantee a good robustness subject to uncertainties and constraints. The proposed robust strategy is evaluated in a dynamic simulation environment of a variable air volume air-conditioning system in various operation conditions by comparing with a conventional PI control strategy. The robustness analysis of both strategies under different weather conditions is also presented.
Original languageEnglish
Pages (from-to)2650-2658
Number of pages9
JournalEnergy Conversion and Management
Issue number10
Publication statusPublished - 1 Oct 2009


  • Air-conditioning system
  • Robust model predictive control
  • Robustness
  • Time-delay uncertainty

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology

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