基于简约空间序列二次规划算法和混合求导方法的精馏塔操作优化

以开放式方程建立精馏塔严格机理模型,对精馏塔的操作优化进行了研究.根据精馏塔操作优化命题自由度低、模型结构稀疏且导数难以解析求解的特点,提出了基于简约空间序列二次规划算法（SQP）和混合求导方法相结合的精馏塔操作优化计算方法.在该方法中优化命题采用简约空间SQP算法求解,求解过程中需要的导数信息采用解析表达和预处理的自动微分技术求取.计算结果表明,本文方法在计算效率上大大高于基于差分求导的标准SQP算法,有利于在线实时优化的实施.另外本文优化结果也表明,精馏塔操作优化对提高产品产量、提高综合经济效益具有明显作用.     

大规模化工过程优化中的SQP-filter算法

逐次2次规划法(SQP)是目前求解非线性约束问题十分有效的方法,但一般都采用罚函数进行线性搜索,这使得它有了很大的限制性,Roger Fletcher和Sven Leyffer等提出了一种filter SQP优化方法,在充分研究这种方法的基础上,编制了计算程序,将其应用到化工过程优化中,多种计算实例表明,该算法优于传统的SQP法。     

如何优化离子膜烧碱生产工艺相关探究

传统的离子膜烧碱生产工艺消耗大量原料,且能量消耗量很大。针对这一弊端,采取取消亚硫酸钠处理装置的方法,使脱氯后淡盐水中存在的游离氯通过盐水化盐的程序以尽力减少损耗。原有的生产离子膜烧碱的设备有待改进,需要设立在线监测装置,使落后的工艺方法得到改进,设立标准化的控制指标和优化参数。这些稳定生产系统的方法能够极好地减化操作工艺,并且所生产的产品达到优级的标准。     

在线优化在离子膜氯碱生产中的应用

用基于人工神经网络的混合建模方法,建立了离子膜效率的软测量模型.应用该模型,用复合形法对年产5万吨烧碱离子膜车间的膜效率进行在线优化,取得了可观的经济效益.     

精馏塔联立优化的简约空间SQP算法

引言采用面向开放式方程的联立算法求解精馏塔优化问题,可以使模拟计算和寻优搜索在同一层迭代中完成,避免了双层法每一步优化搜索都需进行模型收敛计算的缺点,从而可以大大提高计算效率．而且原则上可任意指定自由变量．无论是模拟计算、操作优化还是设计优化都可以利用这个灵活的计算结构进行解算.高效、可靠的非线性约束最优化算法是实现精馏塔联立优化的关键．在流程模拟和过程系统优化中,序贯二次规划法（SequentialQuadraticProgramming,SQP)因其较高的计算效率而被广泛应用．SQP算法中,每一个迭代步都需要求解一个QP子问题…     

膜洗滤过程模型的在线优化策略及其应用

基于恒收率的时间优化模型,利用膜洗滤过程中在线反馈的数据,创新性地提出"走一步看一步"的优化策略,拓展得到了洗滤过程的即时优化模型。结果表明,采用该模型能够解决膜洗滤过程顶洗起点的在线判断问题,避免了为获取相应参数值进行的离线测试实验,能够为工业生产膜洗滤过程的在线优化与控制提供关键理论支撑。     

基于SQP法的ECSS-化工之星优化模块的解算策略

逐次二次规划算法(SQP)是 目前求解非线性约束优化问 题十分有效的方法 ,是当前 非线性约束优化问题中潮流 性的研究课题,ECSS-化工之 星中的优化模块就是以SQP 法为基础建立的 。本文具体 阐述了ECSS-化工之星通用化 工模拟软件中优化模块的具 体解算策略 。     

大型氨碱厂装置循环水水质的优化

详细介绍了连云港碱厂装置循环水优化过程，对比水质优化前后工艺流程特点，指出了采用不停车化学清洗、预膜等措施实现闭路循环，提高换热设备效率，减少设备腐蚀。     

一种化工过程优化的稀疏SQP算法

根据开放式方程模型结构统一、所得优化命题普遍稀疏的特点 ,提出了一种稀疏SQP算法 .利用一阶 /二阶导数构造Hessian矩阵 ,保持了系统的稀疏结构 .通过一个预处理过程获得命题的稀疏结构信息 ,显著减少构造高维矩阵所需工作量 .计算示例表明 ,该算法优于传统SQP法 ,也表明该算法的有效性     

基于SQP的中药生产双效浓缩过程优化

针对中药生产双效浓缩过程动态平衡及蒸发速度优化问题,采用了基于SQP的优化与序贯模块模拟相结合的不可行路径求解方法.实践结果表明,将以SQP为优化核心的不可行路径法求解的优化结果应用在中药生产浓缩过程的自动控制中,能使中药生产过程始终维持双效动态平衡,且蒸发快速和稳定.     

A hybrid GA–SQP optimization technique for determination of kinetic parameters of hydrogenation reactions

A hybrid optimization technique, GA–SQP, is developed in which the genetic algorithm (GA) which is a stochastic method is combined with the sequential quadratic programming (SQP) method which is a deterministic method. This method was used to determine the kinetic parameters of the set of highly nonlinear hydrogenation reactions. Catalyst deactivation was also taken into account. The ability of GA and SQP in solving this type of problem was investigated. It was shown that although the SQP is fast, it is not able to solve this problem properly and is very sensitive to the choice of initial point. The GA was able to solve the problem after a large number of generations. It was shown that the new GA–SQP hybrid method is able to determine the final solution considerably faster than the GA while it is not sensitive to the initial point.     

A Mixed Coding Scheme of a Particle Swarm Optimization and a Hybrid Genetic Algorithm with Sequential Quadratic Programming for Mixed Integer Nonlinear Programming in Common Chemical Engineering Practice

In this paper, mixed integer nonlinear programming (MINLP) is optimized by PSO_GA–SQP, the mixed coding of a particle swarm optimization (PSO), and a hybrid genetic algorithm and sequential quadratic programming (GA–SQP). The population is separated into two groups: discrete and continuous variables. The discrete variables are optimized by the adapted PSO, while the continuous variables are optimized by the GA–SQP using the discrete variable information from the adapted PSO. Therefore, the population can be set to a smaller size than usual to obtain a global solution. The proposed PSO_GA–SQP algorithm is verified using various MINLP problems including the designing of retrofit heat exchanger networks. The fitness values of the tested problems are able to reach the global optimum.     

混合免疫算法及在相平衡计算中的应用

带或不带化学反应的相平衡计算为化学、化工领域的重要课题;可将其转换为带有约束的Gibbs自由能最小化问题。常用的序贯二次规划（SQP）收敛速度快;但依赖初始值;易陷入局部极小。人工免疫算法（AIS）具有全局寻优功能;但局部搜优性能差;收敛速度很慢;甚难找到痕量解。为此;在AIS算法中引入SQP操作;汲取两者的优点;构建混合免疫算法（HAIS）。还将相平衡的物质的量变量转换为摩尔分数;并采用适当策略处理约束;以基本可行解为基础;快速生成满足约束的抗体;以提高HAIS的操作速率。多个相平衡实例应用表明HAIS性能良好;优于其他方法（SQP;AIS）。     

基于流程模拟软件的原油常压蒸馏塔的节能优化

以Honeywell 公司流程模拟软件UniSim对常压塔进行流程模拟为基础,用软件自带的HoneywellSQP优化器进行优化,能够达到一定的优化效果,但这种优化方法存在优化效率低等缺点.针对这些问题,将Matlab中一种能够提高寻优解的改进遗传算法通过VB程序与Unisim中的常压塔模型进行通讯,通过外接改进的遗传...     

换热网络合成问题的并行BB/SQP混合算法

换热网络合成问题通常可用非凸、非线性、不可微的混合整数非线性规划模型描述。基于GPU的并行计算技术为求解大规模模型提供了高效支撑。针对已有并行SQP算法求解换热网络合成问题中存在二元变量组合数过多、并行SQP算法求解结果严重依赖初值等问题,提出了BB/SQP混合并行算法。该算法采用BB算法代替枚举法,不但大大减少了模型求解中可能的二元变量组合,而且为SQP算法选出了可行的初值,从而提高了算法的求解质量。研究表明,所提出的混合并行算法能够有效求解换热网络合成问题,且并行计算相比串行计算的求解速度显著增加,加速比可达39。     

Interior point SQP strategies for large-scale,structured process optimization problems

Successive quadratic programming (SQP) has been the method of choice for the solution of many nonlinear programming problems in process engineering. However, for the solution of large problems with SQP based codes, the combinatorial complexity associated with active set quadratic programming (QP) methods can be a bottleneck in exploiting the problem structure. In this paper, we examine the merits of incorporating an interior point QP method within an SQP framework. This provides a novel interpretation of popularly used predictor-corrector interior point (IP) methods. The resulting large-scale SQP algorithm, with an interior point QP, also allows us to demonstrate significant computational savings on problems drawn from optimal control and nonlinear model predictive control.     

计算机辅助现有化工过程操作最佳化

应用计算机技术来改进现有化工过程操作,对提高化工企业的经济效益有重要的意义.模拟调优通过计算机辅助过程优化技术寻求过程系统的最佳条件,可以使过程达到最佳运行.本文对基于序贯二次规划的两层法作了改进,在二次规划中引入额外变量,构造了新的二次规划问题,并提出了此规划问题的分解策略,从而保证分解矩阵为奇异时仍能对其进行分解.本文提出的两层次-序贯二次规划法,数值稳定性好,收敛较快.用此算法对合成甲醇过程进行优化计算得到了满意的结果,巳在工业装置上实现.     

Comparison of control algorithms for the blood glucose concentration in a virtual patient with an artificial pancreas

To obtain the most suitable control algorithm for a wearable artificial pancreas, different control algorithms were compared and tested using a Hovorka model. Model predictive control (MPC), linear and nonlinear model forms, proportional integral derivative control (PID), neural-network-based model predictive control (NN-MPC), nonlinear autoregressive moving average (NARMA-L2) and sequential quadratic programming (SQP) were evaluated using the Hovorka model. Due to the fact that modeling of biomedical processes are very complex, to present the most effective control algorithm, various control strategies were needed to application. In the control algorithms, set point tracking and disturbance rejection were performed. With respect to the rise times of the control algorithms, SQP with optimal control had the shortest time, and NARMA-L2 had the longest time. Because the control algorithm connects the glucose meter and the insulin pump in an artificial pancreas, the rise time is the most important parameter. We propose that optimal control with SQP is the most suitable control algorithm to connect the glucose meter and the insulin pump.