A model-based predictive supervisory controller for multi-evaporator HVAC systems

  • Authors:

  • Matthew S. Elliott;Bryan P. Rasmussen

  • Affiliations:

  • Texas A&M University, Department of Mechanical Engineering, College Station, TX;Mechanical Engineering, Texas A&M University, College Station, TX

  • Venue:
  • ACC'09 Proceedings of the 2009 conference on American Control Conference
  • Year:
  • 2009

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Abstract

Multi-evaporator vapor compression cooling systems are representative of the complex, distributed nature of modern HVAC systems. Earlier research efforts focused on the development of a decentralized control architecture for individual evaporators that exploits the constraint-handling capabilities of model predictive control while regulating the pressure and cooling setpoints. This paper presents a global controller that generates the setpoints for the local controllers; this controller balances the goals of cooling zone temperature tracking with optimal energy consumption. To accommodate the inherent limitations of the system, a Model Predictive Control (MPC) based approach is used. The improved efficiency and the effects of the tuning parameters are demonstrated upon an experimental system.