用于溶剂回收装置的混合建模和优化方法

润滑油生产中溶剂回收过程要消耗大量能量，但这个设备存在大量时滞、强耦合、时变和干扰等，难于在线测量溶剂质量，如何同时保证溶剂质量和节约能耗是一大挑战。本文首先提出了一种非线性预测控制算法用于控制蒸馆塔温度。由于该装置的特殊性，用于能量优化的数学建模和优化方法并不能满足实际需要。因此，提出了一种把数学方法和专家系统方法相结合的混合建模和优化方法，其中用到了智能数据库，数学建模和优化方法，专家系统建模和优化方法，智能报警系统等，以提高装置的运行功能，实际结果证明该方法很成功。

Combined Modeling and Optimization Method for Solvents Recovering Device

The solvent recovering device in lubrication oil production needs a lot of energy, where there exist large stagnancy, strong coupling, time delay and interference etc. How to assure solvents' quality, whose on-line measurement is difficult, and save energy at the same time is a challenge. A nonlinear predictive control algorithm to control tower's temperature of the device is first proposed. Because of the device's specific characteristics, the mathematical model used in energy optimization cannot meet the actual need. Then a combined modeling and optimization method is proposed, which combines mathematical method with expert system method. Intelligent database, mathematical modeling and optimization, expert system modeling and optimization, and intelligent alarming etc, are used to improve the function of the device clearly. The actual production result proves that the method is effective.