基于Matlab的SMB色谱分离过程计算机仿真研究

针对考虑因素全面的SMB综合速率模型，采用有限元方法和正交配点法分别对柱向和吸附剂颗粒径向模型进行离散化，利用Matlab ODE求解器对SMB过程进行了数值求解，并编制了SMB过程仿真软件。在此基础上进行了一个SMB分离实例仿真，分析了切换时间和流量变化对分离性能的影响，验证了SMB过程分离性能的参数敏感性，提出了对系统实施先进控制的必要性。     

基于预测函数控制算法的动态配料系统应用研究

通过分析混凝土搅拌站动态配料系统的控制过程,为提高系统的效率与配料精度和速度,依据动态配料称重系统和定量控制相结合的思想,在系统动态称重配料过程中引入预测函数控制算法(PFC).MATLAB仿真结果表明,预测函数控制类似对操作员经验的模拟,在模型匹配和模型失配时,系统性能良好,稳定后能满意运行,表现出鲁棒性强、响应快,超调量小的特点,便于在工业控制领域推广应用.     

基于预测模型算法控制的动态配料系统仿真分析

模拟人的思维特点,分析混凝土搅拌站动态配料系统的控制过程,在系统动态称重配料过程中引入迭代自学习控制策略和预测模型算法控制(MAC),并对该系统的非线性误差的控制过程进行了分析;MATLAB仿真表明,系统的配料精度和速度都达到要求,在模型匹配时性能良好,在模型失配时依然能满意运行,表现出响应快、鲁棒性强及超调量小的特点.     

一种提高SMB协议代理文件下载性能的方法

采用传统的代理技术实现SMB协议代理时,存在文件下载性能较低的问题.提出了一种基于"代理+监听客户端"架构的SMB协议代理实现方法,将传统SMB协议代理中的文件内容检查转移到服务器中实现,避免了在SMB代理中进行文件缓存和内容检查,有效地提高了SMB代理的文件下载性能.     

模拟移动床过程的软测量建模仿真研究

模拟移动床色谱作为主要的现代吸附分离技术,近年来在石油化工、精细化工、生物制药、食品加工等领域的复杂混合物分离过程中得到越来越多的应用。模拟移动床系统是一种具有强非线性、强耦合、混杂性、分布参数等特征的复杂工程系统,其建模问题一直受到广泛关注。本文提出用神经网络与遗传算法结合的混合建模方法建立SMB色谱分离过程4区流量与组份纯度的软测量模型。为了解决RBF神经网络训练时隐含层节点数选取无依据,只能依靠反复仿真尝试的问题,提出将混合递阶遗传算法与RBF神经网络结合,建立SMB色谱分离过程软测量模型,以较高的精度实现了SMB组份纯度软测量,通过仿真验证了方法的可行性。     

深圳大学中子源核反应堆控制系统

为提高反应堆的安全与操纵性能，设计建成了深圳大学中子源核反应堆控制系统。系统采用双微机组网方式控制反应堆的运行，并通过模拟记录仪显示运行数据和数据变化曲线。通过实验，得出了系统的控制模型，并对控制模型进行了优化处理。系统的控制误差不超过0．5％，调节过程中最大超调量不超过5％。系统具有反应堆安全保护功能，在超限值的情况下，可实现自动紧急停堆。运行结果表明，控制系统能够满足反应堆安全运行的需要。     

双积分系统的鲁棒控制研究

研究开环不稳定的球杆系统的建模和控制,针对建模复杂以及运行过程中参数变化,并存在不确定性因素、不易控制的问题。为简化建模过程以及提高系统的控制性能,提出以拉格朗日微分方程方法建立模型以及鲁棒H∞控制方法对系统进行鲁棒控制,建立了其简洁而符合实际的模型,提高了系统的控制性能与鲁棒性。结果证明,拉格朗日建模方法简单有效,能改善系统的控制性能以及鲁棒性,并能在航空航天、无人机、海底车辆控制等方面具有良好的实用价值。     

局域网文件系统谁最棒

基于Windows NT的NFS服务器,和基于Unix的SMB服务器是两种主要的跨平台文件/打印服务器。在ZD实验室的测试中,NFS的产品比SMB的产品运行速度更快。不过,性能更快并不说明NFS在任何环境下都是最佳的选择:对于那些在Windows PC上进行了巨额投资的大企业来说,SMB家族的产品具有独到的优点。除此以外,SMB和NFS这两种技术之间的几个重要区别,使得SMB和NFS的性能比较变得非常复杂,其中最关键的一点是,服务器产品中自动性能调整工具的不同水平,使得我们很难建立一个绝对公平的比较条件。所以,我们的测试结果只能说是在某次任意的条件下、关于性能方面的一般性结论,而不能认为是对每种产品的精确评估。众多影响性能测试的不利因素     

基于递归神经网络模型预测控制的模型平稳切换

不同生产条件下的控制系统可视多模型控制系统，但多模型控制在模型切换时会引起系统的瞬态响应。采用递归神经网络建立系统的多个模型，基于模型预测控制进行控制模型切换，克服了模型切换时引起的系统瞬态响应，实现系统的平稳切换。并通过仿真表明这种切换策略明显改善了模型切换过程的动态性能。     

基于Trnsys的水冷型中央空调系统建模与仿真

以广州某大厦水冷型中央空调系统为例子,利用Trnsys建立了大厦某层的多区域建筑及其中央空调系统能耗仿真模型,在此基础上分析加控制和不加控制2种情况下中央空调能耗情况。由2种模型的仿真结果可知中央空调具有很大的节能空间。模型主要用于研究中央空调运行的一些性质,对中央空调的节能优化控制具有重要的意义。     

Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose

Chromatographic separations are an expanding technology for the separation of high value products, particularly in the area of pharmaceutics, food, and fine chemicals. The simulated moving bed (SMB) process as a continuous chromatographic separation process is an interesting alternative to conventional batch chromatography, and gained more and more impact recently. The SMB process is realized by connecting several single chromatographic columns in series. A countercurrent movement of the bed is approximated by a cyclic switching of the inlet and outlet ports in the direction of the fluid stream. Because of its complex dynamics, the optimal operation and automatic control of SMB processes is a challenging task. This paper presents the design of a model-based optimization and control scheme for SMB chromatographic separation processes and its application to the separation of fructose and glucose. We propose a two-layer control architecture where the optimal operating trajectory is calculated off-line by dynamic optimization based on a rigorous process model. The parameters of the model are adapted based on online measurements. The low-level control task is to keep the process on the optimal trajectory despite disturbances and plant/model mismatch. Here identification models based on simulation data of the rigorous process model along the optimal trajectory are combined with a suitable local controller. The efficiency of the trajectory control algorithm is shown in a simulation study for the separation of fructose and glucose on an 8-column SMB plant.     

基于Profibus-DP现场总线的多功能色谱分离装置控制系统设计

为了实现多功能色谱分离装置的精准化控制,加速模拟移动床色谱纯化分离速度,设计基于Profibus-DP现场总线的多功能色谱分离装置控制系统;以STM32F103微处理器作为底层控制设备,连接Profibus-DP协议芯片、VPC3与RS-485接口电路,转化从站地址电路与设定应用模块,利用模拟移动床控制回路,完成Profibus-DP现场总线的硬件电路设计;建立梯度SMB色谱,采用异步切换方式,控制变浓度进料的实际操作行为,分离处理模拟移动床多功能色谱,结合多功能色谱分离装置的控制原理,运用气相色谱法,分析色谱分离过程中的基质效应形式,实现多功能色谱分离装置控制系统软件设计;实验结果表明,基于Profibus-DP现场总线控制系统的模拟移动床色谱纯化分离速度较快,能够有效满足多功能色谱分离装置精准化控制的操作需求.     

Cycle to cycle adaptive control of simulated moving bed chromatographic separation processes

The simulated moving bed (SMB) technology is increasingly applied in various fields, ranging from the food to the pharmaceutical sectors, for the chromatographic separation of fine (bio)chemicals. In this study, an adaptive controller acting on the fluid flow rates and commutation period is used to regulate the spatial location of the adsorption and desorption waves, and in turn the purity and productivity of the raffinate and extract effluents. This controller is based on a simple discrete-time model of the concentration fronts movement, derived from wave theory. A simple parameter adaptation scheme makes this controller robust to parameter uncertainties and drifts, and allows process start-up with minimum a priori knowledge of the separation parameters. In this study, the performance of the controller is demonstrated for two different applications: the separation of fructo-oligosaccharides (linear isotherms) and cyclopentanone–cycloheptanone (competitive Langmuir isotherms). Different plant/sensor configurations are also examined, indicating the potential of the control strategy even with reduced measurement information.     

Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives

A new bi-objective genetic programming (BioGP) technique has been developed for meta-modeling and applied in a chromatographic separation process using a simulated moving bed (SMB) process. The BioGP technique initially minimizes training error through a single objective optimization procedure and then a trade-off between complexity and accuracy is worked out through a genetic algorithm based bi-objective optimization strategy. A benefit of the BioGP approach is that an expert user or a decision maker (DM) can flexibly select the mathematical operations involved to construct a meta-model of desired complexity or accuracy. It is also designed to combat bloat – a perennial problem in genetic programming along with over fitting and under fitting problems. In this study the meta-models constructed for SMB reactors were compared with those obtained from an evolutionary neural network (EvoNN) developed earlier and also with a polynomial regression model. Both BioGP and EvoNN were compared for subsequent constrained bi-objective optimization studies for the SMB reactor involving four objectives. The results were also compared with the previous work in the literature. The BioGP technique produced acceptable results and is now ready for data-driven modeling and optimization studies at large.     

Automatic control of the simulated moving bed process for C8 aromatics separation using asymptotically exact input/output-linearization

An approach to automatic control of the simulated moving bed process (SMB) applied to the separation of C₈ aromatics is presented. The principle of asymptotically exact input/output-linearization is used. The controller is based on a nonlinear state estimator using the true moving bed model (TMB). The estimator receives measurement data from four spectroscopic measurement cells. The problem of moving measurement positions with respect to the TMB model is addressed. An exactly linearizing feedback of the estimated states is designed using the nonlinear TMB model equations. The performance of the controller is shown in simulations using a detailed SMB model as a representative of the real process.     

SMB色谱分离过程的Matlab仿真

基于考虑因素全面的综合速率模型,通过对柱向和吸附颗粒径向模型采用有限元法和正交配点法进行离散化,利用Matlab ODE求解器对离散化得到的常微分方程进行数值求解,在此基础上设计了仿真软件。以具体仿真实例,验证了所用方法的可行和有效性。最后分析了切换时间和流量变化对分离性能的影响。     

Neural network-based identification of SMB chromatographic processes

In this contribution, the identification problem for the control of nonlinear simulated moving bed (SMB) chromatographic processes is addressed. For process control the flow rates of extract, desorbent, and recycle of the SMB process, and the switching time are the manipulated variables. But these variables influence the process in a strongly coupled manner. Therefore, a new set of input variables is introduced by a nonlinear transformation of the physical inputs, such that the couplings are reduced considerably. The front positions of the axial concentration profile are taken as model outputs. Multilayer feedforward neural networks (NN) are utilized as approximating models of the nonlinear input–output behavior. The gradient distribution of the model outputs with respect to the inputs is used to determine their structural parameters and the network size is chosen by the SVD method. To illustrate the effectiveness of the identification method, a laboratory scale SMB process is used as an example. The simulation results of the identified model confirm a very good approximation of the first principles models and exhibit a satisfactory long-range prediction performance.     

A practical multiple model adaptive strategy for single-loop MPC

This paper details a multiple model adaptive control strategy for model predictive control (MPC). To maintain performance of this linear controller over a wide range of operating levels, a multiple model adaptive control strategy for dynamic matrix control (DMC), the process industry's standard for MPC, is presented. The method of approach is to design multiple linear DMC controllers. The tuning parameters for the linear controllers are obtained using novel analytical expressions. The controller output of the adaptive DMC controller is a weighted average of the multiple linear DMC controllers. The capabilities of the multiple model adaptive strategy for DMC are investigated through computer simulations and an experimental system.     

煮糖结晶过程的动态矩阵控制研究

由于煮糖结晶过程本身受干扰的因素比较多，如糖浆的锤度、糖浆杂质、真空度以及温度的变化都会影响蔗糖结晶过程，非线性比较强。因此一般的控制策略（比如常规PID）难以凑效，根据煮糖结晶过程的物料平衡、能量平衡和生产过程的各种物性参数的机理解析关系（如晶体生长分散）建立描述被控对象的模型，并以该模型作为预测模型对煮糖结晶过程实施动态矩阵控制（DMC）．仿真结果表明该控制算法对煮糖过程的控制是有效的。