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 whi...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.展开更多
基金supported by National Natural Science Foundation of China (Nos. 61233004, 61221003, 61374109 and 61473184)National Basic Research Program of China (973 Program)(No. 2013CB035500)+1 种基金partly sponsored by the Higher Education Research Fund for the Doctoral Program of China (No. 20120073130006)National Research Foundation of Singapore (No. NRF2011 NRF-CRP001-090)
文摘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.
