基于图模型的间歇过程误操作风险辨识

提出了一套基于图模型的建模方法,该模型以Petri网和符号有向图（SDG）为基础将模型分为上部和下部,加入操作点、控制库所、判断模块等模型元素,并结合间歇过程的特点,提出了关联变量、目标变量检查表、操作点检查表和关联变量检查表等概念。根据误开误关、过早过晚、步骤添加删除等误操作,对模型进行验证。验证结果表明,该模型解决了先前方法难以描述具体操作的缺陷,并且模型结构简单,具有整体性。不仅能够方便地描述3种不同类型的误操作,还能有效地对误操作进行风险辨识,具有一定的适用性。     

间歇过程自动化的进展

本文从控制角度分析间歇过程的特征，并介绍了间歇控制装置和控制软件的现状和发展趋势，特别是配方管理和生产调度在线应用。     

间歇结晶过程的分析

本文概要地介绍了用于研究在间歇悬浮结晶器中的结晶动力学和晶体粒度分布（CSD）的实验技术和数据分析的新进展,讨论了包括最大CSD的特征化、累积CSD方法、热响应技术、最大允许成长速率在内的几个简单而有用的方法。     

间歇生产过程的自动控制

本文简要介绍了间歇生产过程及其特点,结合间歇生产过程对控制的要求,提出了相应的自动控制方案。阐述了间歇生产过程自动化的实现方法。     

间歇化工过程与计算机应用

首先指出间歇过程是一门独立的、有自身特点的、在化学工业中具有独特地位的学科。然后扼要回顾了计算机在间歇过程设计和生产调度中的应用，并介绍了几个典型的用于间歇过程的软件。最后简单介绍了由ＩＳＡ颁布的间歇控制标准ＳＰ８８，以便读者了解该领域的最新国际动态     

基于多向核熵成分分析的微生物发酵间歇过程监测研究

针对微生物发酵间歇过程监测算法只考虑数据信息最大化未考虑数据簇结构信息的不足,提出了基于多向核熵成分分析(Multi-way Kernel Entropy Component Analysis,MKECA)间歇过程监测的新方法。该方法首先引入AT展开策略对三维历史数据进行预处理,然后通过核映射将数据从低维空间映射到高维特征空间,解决数据的非线性特性,并在高维特征空间依据核熵的大小对数据进行降维,使降维后的数据能够最大化地保留原始数据的分布;同时理论证明了所提方法在特定条件下等同于传统方法,也就是说MKECA既能兼顾传统方法的优势,又能弥补传统方法的不足;最后通过青霉素仿真数据进行验证,表明MKECA方法具有更可靠的监控性能,能及时、准确地监测出故障。     

间歇生产过程的控制系统

论述了间歇生产过程控制的特点、硬件系统的选择原则和软件的开发方法及功能 ,并具体介绍了一个间歇精细化工的特殊生产过程控制的实例 ,对从事间歇生产过程控制开发、设计工作的人员 ,具有实用参考价值     

基于MKPLS和SQP方法的间歇过程迭代优化控制

采用多向核偏最小二乘（MKPLS）方法建立间歇过程的模型并进行操作条件的优化。由于存在模型失配和未知扰动,基于MKPLS模型的最优控制轨迹在实际对象上往往难以实现最优的产品质量指标。本文利用间歇过程批次间的重复特性与序贯二次规划（SQP）优化算法中迭代计算的相似特点,提出了一种基于MKPLS模型的批次间优化调整策略,使得经过逐步优化调整得到的控制轨迹作用于实际对象时,可以得到更优的质量指标。该方法的有效性在苯乙烯聚合反应器和乙醇流加发酵过程的仿真对象上得到了验证。     

浅谈玻璃混合料生产的三大过程

介绍了混合料生产的三大过程,提出其中存在的问题和解决的措施。强调了三大过程都要重视,不可偏废,确保优质合格的混合料供应大窑。     

FEASIBILITY OF ON-LINE REOPTIMIZATION IN BATCH PROCESSES

This work points out some serious drawbacks of the standard procedure for on-line optimization of batch processes. Commonly, at any given batch time, on-line measurement information is used to improve the estimate of the current state and the objective function is optimized again based on the estimated state. This strategy is useful when only the initial state is in error, but is unreliable in the more common case of an inaccurate dynamic model. Reoptimization based on the state estimates may then constitute a poor policy, even if perfect state estimates were available. Simulation examples of a semi-batch reactor are used to illustrate the associated pitfalls and to demonstrate what can be done to possibly detect and circumvent them.     

间歇过程优化与先进控制综述

总结近年来间歇过程操作优化和设计优化中出现的各种新方法,以及在优化问题求解中使用的各种先进控制策略,反映间歇过程最优化和先进控制的最新研究方向。重点介绍间歇过程单元的操作优化和控制,兼顾在线稳态优化和动态优化。对新的研究方法提出展望。     

THE GENERATION OF CONTROL STEPS IN BATCH PROCESSES BY USING AI TECHNIQUES

A new method for the generation of control steps in batch processes is presented in this paper. One of the AI techniques, namely, the key word analysis technique is used to process the master recipe and the corresponding equipment units. The control steps are created according to the process information specified in the master recipe and the properties of the existing equipment unit. The aim is to unambiguously specify the control steps using a set of basic control instructions from which the actual control code could be created.     

间歇化工过程和模型优化调度

Chemical batch processes have become significant in chemical manufacturing.In these processes,large numbers of chemical products are produced to satisfy human demands in daily life.Recently,economy globalization has resulted in growing worldwide competitions in traditional chemical process industry.In order to keep competitive in the global marketplace,each company must optimize its production management and set up a reactive system for market fluctuation.Scheduling is the core of production management in chemical processes.The goal of this paper is to review the recent developments in this challenging area.Classifications of batch scheduling problems and optimization methods are introduced.A comparison of six typical models is shown in a general benchmark example from the literature.Finally,challenges and applications in future research are discussed.     

基于改进多模型FDA的间歇生产过程的故障诊断

1 INTRODUCTION In recent decades, batch processes have been a wide concern in the chemical fields because of their low-volume, high-value products and capabilities of easily tracking changing market situations. Therefore, it is necessary to monitor them in order to ensure safe, decrease the production costs and enhance the quality of products. Batch processes are characterized by the precise sequencing and automation of all stages in the sequence. They convert raw materials into products …     

Deterministic vs. stochastic performance assessment of iterative learning control for batch processes

The performance assessment of linear time‐invariant batch processes when iterative learning control (ILC) is implemented has been discussed. Previous literatures show that conventional performance assessment cannot be directly applied to batch processes due to the nature of batch operations. Chen and Kong have suggested a new method to assess the control performance of batch processes using optimal ILC as the benchmark. In their work, ILC controllers are assumed to affect either stochastic or deterministic performance but without considering their interaction. This work elaborates the controllers effects on both stochastic and deterministic control performance of batch processes. It is shown that the optimal solution based on the minimum variance control law has a trade‐off between deterministic and stochastic performance, which can be shown by a trade‐off curve. Furthermore, a method is proposed to estimate this curve from routine operating data, against which the performance of ILC controllers can be assessed. Simulation studies are conducted to verify the proposed method. © 2012 American Institute of Chemical Engineers AIChE J, 59: 457–464, 2013