关键词: 变风量空调系统, 模型预测控制, 压差控制, 线性矩阵不等式, 鲁棒性, 优化

Abstract: The secondary pump differential pressure control in the Variable Air Volume（VAV） air conditioning system can effectively reduce energy consumption. In order to overcome secondary pump model uncertainty, and improve the response speed and precision of secondary pump frequency control, it uses robust Model Predictive Control（MPC） strategy based on the Linear Matrix Inequality（LMI）. The algorithm can be divided into offline and online parts. The upper bound of the objective function is set as a known quantity which is obtained by offline algorithm, and re-optimizes to get a sequence of asymptotically larger stable invariant ellipsoid sets. According to the measured current state variables online at each sampling period, the position of the state variables can be accurately located to obtain the system control variable by three adjacent ellipsoid sets. In this paper, the online optimization theory is proven rigorously. Simulation results indicate that the algorithm is more effective than traditional algorithm. The experiment results of secondary pump differential pressure control show that the new algorithm can get bigger feasible domain, faster system response and better control effect.

Key words: variable air volume air conditioning system, model predictive control, differential pressure control, linear matrix inequality, robustness, optimization