Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.
本文将近年来关于网络化分布式预测控制(distributed model predictive contro,DMPC)设计的结果进行了总结概述.DMPC不仅仅继承了预测控制的优点而且还有分布式控制框架的特点.首先,介绍了分布式控制的系统结构设计;然后,依据预测控制中的性能指标,从3个方面对DMPC进行了介绍:基于局部性能指标的DMPC,基于邻域指标的DMPC和基于全局指标的DMPC.最后,选取3个典型例子来说明一些DMPC的有效性.
