Rapid Prototyping for Photochemical Reaction Engineering

This contribution gives an overview of the general aspects of photochemical reaction engineering, discusses these aspects in the context of rapid prototyping and evaluates the constraints of current additive manufacturing technologies. Subsequently, possible approaches to utilize the benefits of rapid prototyping for process intensification of photochemical reactions are described. Furthermore, the advantageous application of rapid prototyping is demonstrated with the help of four examples.     

Optimal model-based aeration control policies in a sequencing batch reactor

We present a non-linear programming formulation for the computation of optimal aeration policies in a sequencing batch reactor for wastewater streams treatment. We assume that organic matter and nitrogen are the main pollutants to be removed to meet water quality targets. The novelty of the work lies in the fact that no binary variables are required to compute the switching time between the aerobic and anoxic stages of the water treatment process leading to a simpler, robust and easier to compute optimization formulation. Moreover, because the control valve, through which air is fed to the reactor, can take either its minimum or maximum bounds as well as any fractional values between such bounds, improved optimal aeration profiles are reported. Such improved profiles mean that shorter processing times are required, compared to previous solutions, leading also to a reduction in the operation cost of the wastewater treatment process. Although the optimal operation policies were computed for a typical home wastewater stream, the optimization formulation can also be extended for the treatment of other polluted streams.     

基于电化学沉积的快速成型控制系统设计

利用电化学沉积原理,设计了能够快速成型金属材质模型的快速成型控制系统。介绍了控制系统的整体架构、功能模块设计,并阐述了控制系统软件的关键算法。通过输入三维模型,该控制系统能够实现需求模型的快速成型。     

Nonlinear PI controllers with output transformations

Well‐designed nonlinear proportional‐integral (PI) controllers are successful for nonlinear dynamical processes like linear PI controllers are for linear processes. Two nonlinear blocks representing proportional and integral terms can be designed so that the linearized controllers perform the same as linear PI controllers for linearized processes at the given operating points. For some nonlinear processes, nonlinear blocks for nonlinear PI controllers can be singular at some operating points, and control performances can be poor for set points near those points. To mitigate such disadvantages, new nonlinear PI controllers that introduce output transformations are proposed. Several examples are given, showing the performance of the proposed nonlinear PI controllers. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4264–4269, 2015     

Implementation of a block-oriented model library for undergraduate process control courses in EMSO simulator

Process control courses usually have a section of the course focused on the building of block diagrams for modeling, simulation, and analysis of open and closed loop processes. For this purpose, students are often oriented to build models using SIMULINK or XCOS because of the versatility of these powerful tools in the easy construction of mathematical models using the concept of block-oriented programming. In this paper we propose a model library built in the software EMSO that allows the user to create block diagrams for process control studies. EMSO is a powerful tool for process modeling, dynamic simulation and optimization, freely available for academic purpose. With the developed library, analysis of systems responses, even for complex processes, can be carried out and PID controller tuning tasks are made easier and less time-consuming to the students, allowing them to advance in the study of more complex control strategies such as ratio, cascade, override, feedforward, among others. Students valued the developed tool as a very useful and practical one to favor a control course learning process and between equivalent and advantageous tool when compared with SIMULINK and XCOS.     

Nonlinear Model Algorithmic Control of a pH Neutralization Process

Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control （MAC） strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm （named NLH-MAC） is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative （PID） controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors.     

Investigating Control Schemes for an Ideal Thermally Coupled Distillation Column (ITCDIC)

The control schemes of an ITCDIC are addressed. A modified IMC scheme (M‐IMC) is proposed to overcome model/plant mismatch of the Internal Model Control scheme (IMC). Predictive PID control (P‐PID) and Adaptive Predictive control (AP‐PID) schemes are also presented to improve effectively the response speed of the multi‐loop PID control (M‐PID) and eliminate its residual error. A detailed comparative investigation on the above five control schemes was performed. Simulation results demonstrate all the schemes are able to keep two end products within their specifications. M‐IMC is the best one with the fastest response speed. AP‐PID is the second choice since it is better at dealing with sudden set‐point transitions and complex external disturbances than P‐PID. M‐PID cannot compete with AP‐PID and P‐PID due to its slow servo response speed and large residual error. IMC ranks last as it is extremely sensitive to changes in the operating conditions.     

基于APSO的非线性预测控制及在pH中和反应中的应用

提出一种基于自适应粒子群优化的预测控制算法,得益于APS0的全局最优和快速收敛的特点,可以有效地克服常规优化算法的不足.将此算法应用于中和反应过程的pH值控制中,仿真结果显示了该方法的有效性.     

Model predictive control for the self-optimized operation in wastewater treatment plants: Analysis of dynamic issues

This paper describes a procedure to find the best controlled variables in an economic sense for the activated sludge process in a wastewater treatment plant, despite the large load disturbances. A novel dynamic analysis of the closed loop control of these variables has been performed, considering a nonlinear model predictive controller (NMPC) and a particular distributed NMPC-PI control structure where the PI is devoted to control the process active constraints and the NMPC the self-optimizing variables. The well-known self-optimizing control methodology has been applied, considering the most important measurements of the process. This methodology provides the optimum combination of measurements to keep constant with minimum economic loss. In order to avoid nonfeasible dynamic operation, a preselection of the measurements has been performed, based on the nonlinear model of the process and evaluating the possibility of keeping their values constant in the presence of typical disturbances.     

流程工业清洁生产对过程控制的挑战

分析清洁生产方式对过程控制带来的新问题,从流程企业清洁生产所具有的物料循环和热集成等过程特点出发,围绕着过程特性分析、过程设计与控制的综合、控制系统结构设计和控制算法等几方面综述清洁生产过程控制的研究进展,并提出清洁化生产中一些值得重视的过程控制研究课题.     

Simultaneous process and control system design for grade transition in styrene polymerization

We present a comprehensive approach to the simultaneous design and control of a continuous stirred tank reactor (CSTR) for styrene solution polymerization that must be able to produce different polymer grades. The resulting tool allows simultaneous selection of the polymerization equipment, the multivariable feedforward-feedback controller's structure and tuning parameters, the steady states and the transition paths between them. For this purpose a multiobjective optimization is implemented to minimize the annualized reactor cost, the operating costs, the production of off-specification polymer and the transition time between steady states. Trade-offs between the sometimes conflicting objectives are dealt with by the optimization. Unlike many previous grade transition studies, steady states are not known a priori. The only known parameters are the target molecular weights to be produced at each steady state. We have analyzed three different scenarios, and propose practical criteria for selecting the most reasonable optimum when the solution is not unique.     

瓦窑堡油田羊马河区调剖技术研究

瓦窑堡油田羊马河区位于陕西省子长县境内,构造位置处于鄂尔多斯盆地陕北斜坡的中东部。主力油层为长2层。油层具有储油物性较好,油藏整装连片,油藏丰度大等特点。但油藏同样具有低孔、低渗、低含油饱和度的特点,属于地质构造活动较弱的岩性油藏。经过多年来的注水开发作业,该区已经取得不错的产量,但同时也带来了很多问题,岩石孔隙经过长年的冲刷已经形成大孔道,注入水将沿着大孔道从注水井流入采油井,其余含油孔隙将无法被驱出,使得产油量大幅度直线下降。为此,采用调剖堵水技术,将大孔道封堵,注入水进入含油孔隙,使油井达到高产、稳产的目的,进一步提高采收率。     

Modeling,Control, and Optimization of Ideal Internal Thermally Coupled Distillation Columns

Internal Thermally Coupled Distillation Columns (ITCDIC) are the frontier of energy saving distillation research. In this paper, the ideal ITCDIC is considered. A novel mathematical model and a related simulation algorithm are proposed. The dynamic responses of open‐loop, PID controllers and the responses of closed‐loops are carried out. The results show that the ITCDIC is a self‐balance process and could be operated smoothly with two PID controllers; the steady‐state optimization met the need of ITCDIC optimization. Furthermore, a steady‐state optimization model of the operation parameters is presented, which can be used to directly obtain the optimal operation parameters simultaneously guaranteeing not only the product quality and the maximum energy savings but also the dynamic operability and controllability. The benzene‐toluene system is studied as an illustrative example.     

Nonlinear Optimization Strategies for Process Separations and Process Intensification

Advanced nonlinear programming (NLP) strategies based on equation-oriented (EO) process models are leading to significant improvements in computer-aided process engineering. The EO paradigm allows the development of large, integrated optimization platforms that expand the scope of continuous optimization tasks in process engineering. In particular, these platforms deploy significantly faster NLP strategies than in commercial simulation tools. Moreover, they exploit exact derivatives and system structure in order to consider much larger and more challenging systems. Finally, they allow the incorporation of much more general models, such as multi-level optimization and complementarity constraints. For process optimization this allows the treatment of extended models for complex phase equilibrium and process separations. These advances facilitate the optimization of novel integrated systems that arise in process intensification. Several separation case studies are presented that illustrate these optimization concepts and demonstrate their effectiveness for hybrid membrane/distillation separations and reactive distillation systems that typify novel systems in process intensification.     

甲醛化工厂危险工艺改造中的自控设计

危险工艺改造现已全面实施,现就其中一个项目的改造情况浅谈自控部分改造方案。     

A Procedure for Feasible and Optimal Operational Strategies for Control of CARE Systems

In Biochemical Engineering, the downstream stage to recover and purify product obtained from fermentation plays a central role in the commercial success of the process. Previously, the continuous adsorption recycle extraction (CARE) process was optimized using experimental design and surface response analysis. Such an approach did not require the use of reduced models. Thus, through a detailed model of the system and extensive simulation, operational restrictions, the whole set of process variables and design details in the analysis were accounted for. Through this procedure, a new optimal set-point was applied to the control algorithm developed to give higher system performance. The appropriate manipulated variable was determined from the dynamic responses and control strategies could be defined. The classical proportional integral (PI) and proportional integral derivative (PID) feedback and non-conventional feedback-feedforward controllers were studied. The results show that the performance was good even with time delays up to 24 and 36 min, respectively. © 1997 SCI.     

Nonlinear dynamic process monitoring based on dynamic kernel PCA

Nonlinear dynamic process monitoring based on dynamic kernel principal component analysis (DKPCA) is proposed. The kernel functions used in kernel PCA (KPCA) are profitable for capturing nonlinear property of processes and the time-lagged data extension is suitable for describing dynamic characteristic of processes. DKPCA enables us to monitor an arbitrary process with severe nonlinearity and (or) dynamics. In this respect, it is a generalized concept of multivariate statistical monitoring approaches. A unified monitoring index combined T² with SPE is also suggested. The proposed monitoring method based on DKPCA is applied to a simulated nonlinear process and a wastewater treatment process. A comparison study of PCA, dynamic PCA, KPCA, and DKPCA is investigated in terms of type I error rate, type II error rate, and detection delay. The monitoring results confirm that the proposed methodology results in the best monitoring performance, i.e., low missing alarms and small detection delay, for all the faults.     

Regulation of film thickness, surface roughness and porosity in thin film growth using deposition rate

This work focuses on distributed control of film thickness, surface roughness and porosity in a porous thin film deposition process using the deposition rate as the manipulated input. The deposition process includes adsorption and migration processes and it is modeled via kinetic Monte Carlo simulation on a triangular lattice with vacancies and overhangs allowed to develop inside the film. A distributed parameter (partial differential equation) dynamic model is derived to describe the evolution of the surface height profile of the thin film accounting for the effect of deposition rate. The dynamics of film porosity, evaluated as film site occupancy ratio, are described by an ordinary differential equation. The developed dynamic models are then used as the basis for the design of a model predictive control algorithm that includes penalty on the deviation of film thickness, surface roughness and film porosity from their respective set-point values. Simulation results demonstrate the applicability and effectiveness of the proposed modeling and control approach in the context of the deposition process under consideration.     

模糊控制在联碱碳化过程中的应用研究

利用模糊控制算法 ,适当集成一些专家经验 ,比较可行地对联碱碳化过程进行了控制和优化 ,使生产过程更加平稳 ,明显提高了生产指标。本文提出的优化解决方法 ,对于许多具有相似特点的生产过程的控制和优化 ,同样具有积极意义     

基于广义预测控制的间歇生产迭代优化控制

针对间歇生产,提出了一种基于广义预测控制的批次迭代优化控制策略--BGPC,在间歇过程中引入批次间优化的思想,将迭代学习控制ILC和广义预测控制GPC相结合,在GPC实时结构参数辨识的基础上利用前面批次的模型预测误差修正当前批次的模型预测值.该算法能够有效地克服模型失配、扰动和系统参数变化等情况.文章最后以一个数值例子和间歇反应器为对象进行仿真试验,验证了该算法是有效的.