As an excellent solvent, ionic liquids (ILs) have received much attention in the last two decades. One of the most important applications is to be used as an extractant for separation of azeotropic mixtures via extractive distillation (ED). In this work, 1-ethyl-3-methylimidazolium dicyanamide ([emim][N(CN)2]) is selected as the extractant to separate isopropanol (IPA)-water azeotrope based on two ED processes. Multi-objective genetic algorithm (MOGA) is used to determine the operating parameters for these ED processes. Total annual cost (TAC), efficiency indicator of extractive section (E_ext), efficiency indicator of per tray in extractive section (e_ext) and energy consumption per product flow rate (GEC) are selected as objective functions in the ED process optimization, and the Pareto front provides a series of solutions satisfying the constraints with different operating parameters. The results show that TAC of the process 2 with two evaporators used in the phase of solvent recovery is 4.26% lower than that of process 1 with one evaporator. In addition, the thermodynamic efficiency (η) and CO₂ emissions are calculated for different cases, and they provide the reference for the selection of operating parameters. On this basis, the control structures of ED processes are further studied, and the traditional two-point temperature control structure works pretty well for disturbances of both feed rate and feed composition.

作为一种极好的溶剂，离子液体（ILs）在过去的二十年中受到了广泛的关注。最重要的应用之一是用作通过萃取蒸馏（ED）分离共沸混合物的萃取剂。在这项工作中，基于两种ED工艺，选择1-乙基-3-甲基咪唑鎓双氰胺（[emim] [N（CN）2]）作为萃取剂，以分离异丙醇（IPA）-水共沸物。多目标遗传算法（MOGA）用于确定这些ED过程的操作参数。总年度费用（TAC），萃取部分（的效率指标ë _EXT），在萃取区（每盘的效率指标ë _EXT）和每产物流速的能量消耗（GEC）被选为ED工艺优化中的目标函数，而Pareto前沿提供了一系列满足不同操作参数约束条件的解决方案。结果表明，在溶剂回收阶段使用两个蒸发器的方法2的TAC比使用一个蒸发器的方法1的TAC低4.26％。此外，还针对不同情况计算了热力学效率（η）和CO ₂排放量，它们为选择运行参数提供了参考。在此基础上，对ED工艺的控制结构进行了进一步的研究，传统的两点温度控制结构对进料速度和进料组成的扰动都起到了很好的作用。