Model Predictive Control for Vapor Compression Cycle of Refrigeration Process

A model predictive controller based on a novel structure selection criterion for the vapor compression cycle (VCC) of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control (MPC) strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig. © 2016, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature.