基于量子行为的模拟移动床的操作优化  

Operation Optimization of Simulated Moving Bed Based on Quantum Behavior

作　　者：李凌 邓家璧 袁德成 LI Ling;DENG Jia-bi;YUAN De-cheng(College of Information Engineering,Shenyang University of Chemical Technology,Shenyang 110142,China)

机构地区：[1]沈阳化工大学信息工程学院,沈阳110142

出　　处：《华东理工大学学报（自然科学版）》2018年第4期511-517,共7页Journal of East China University of Science and Technology

基　　金：国家自然科学基金(60874057);国家高技术研究发展计划(863)重点资助项目(2008AA042902)

摘　　要：模拟移动床是一种能实现连续分离的装置,由于模拟移动床模型复杂,性能指标众多,因此需要智能算法对模拟移动床的性能指标进行优化。本文运用遗传算法、粒子群算法对模拟移动床线性吸附等温线下的性能指标进行单目标优化,并利用加入量子行为的粒子群和遗传算法作比较,证明了量子理论在解决模拟移动床优化问题的优越性,然后运用NSGAII算法、MOPSO算法对模拟移动床线性吸附等温线下的性能指标进行多目标优化和对比实验,仿真结果验证了所用方法的有效性。The simulated moving bed （SMB） chromatography has been used extensively as a main modern separation technology for the complex separation tasks in the areas of petroleum chemicals, fine chemicals, pharmaceuticals, and food processing in recent years. Compared with the conventional batch chromatographic separation process, the simulated moving bed chromatography is preferred for its continuous operations. The SMB technology has the advantage of significantly lower solvent and solid phase consumption while delivering higher purity and productivity. It also achieves a faster scale-up production especially for the separation of homologues and chiral enantimers which are difficult to separate. The simulated moving bed process is a highly sophisticated hybrid process that includes both continuous and discrete variables. The separation effects are subject to the influence of operation parameters such as the absorption isotherm, column characteristics, the feed concentration, feed ingredient, temperature, and switch time, between which complex dynamics as well as strong couples exist. These influence factors inevitably increases the experiment cycle, and makes the process modeling, operation optimization, and industry enlargement extremely difficult. Moreover, the simulated moving bed process is highly sensitive and uncertain to external disturbances and the establishment and implementation of robust control methods for the SMB process is also a potential research area. The difficulty of applying conventional feedback control to the SMB process lies not only in its non-linearity, the cyclical stable state, the presence of both continuous and discrete variables, but also in the large time delays to disturbances. Therefore, the modeling and optimization research of the simulated moving bed separation process not only has important theoretic values and enormous economic benefits. Due to the complexity of simulated moving bed model and performance index of diversity, intelligent algorithm is used to optimize performance

关 键 词：模拟移动床 多目标优化 GA算法 NSGAII算法 MOPSO算法 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]