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Optimal control analysis and Practical NMPC applied to refrigeration systems.

G Bejarano1, M G Ortega2, J E Normey-Rico3

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Optimal control of refrigeration systems is challenging due to limited inputs. This study proposes a model but finds controllability issues prevent achieving maximum efficiency, impacting control strategies.

Keywords:
Controllability studyGlobal optimizationModel predictive controlProcess controlRefrigeration system

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Area of Science:

  • Thermodynamics and Refrigeration Systems
  • Control Theory and Engineering

Background:

  • Mechanical compression refrigeration systems are crucial for cooling applications.
  • Optimizing their efficiency while meeting cooling demands is a significant engineering challenge.
  • Existing control strategies often struggle to achieve theoretical optimal performance.

Purpose of the Study:

  • To develop and analyze a reduced-order state-space model for optimal control of canonical refrigeration cycles.
  • To investigate the controllability of the proposed model in achieving optimal operational states.
  • To compare the performance of a practical Nonlinear Model Predictive Control (NMPC) strategy against a known feedback-plus-feedforward approach.

Main Methods:

  • A reduced-order state-space model based on the moving boundary approach was developed for the canonical refrigeration cycle.
  • Controllability analysis was performed to understand the limitations in achieving optimal cycle variables.
  • Optimization simulations were conducted to evaluate control strategies under varying cooling demands.

Main Results:

  • The optimal refrigeration cycle is defined by three variables but only two control inputs are available, posing a controllability challenge.
  • Optimization simulations revealed that minimum superheating does not always lead to optimal cycles for varying cooling demands.
  • Both practical NMPC and a feedback-plus-feedforward strategy encountered difficulties in reaching the optimal cycle.

Conclusions:

  • The proposed reduced-order model highlights inherent controllability limitations in achieving optimal efficiency for mechanical compression refrigeration systems.
  • Control strategies, including NMPC, may struggle to reach theoretical optimal performance due to these limitations.
  • Further research into advanced control techniques or system modifications may be necessary to overcome these challenges.