Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks

In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.

Batch Process Modelling and Optimal Control Based on Neural Network Model

This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.

Run-to-run product quality control of batch processes

Batch processes have been increasingly used in the production of low volume and high value added products. Consequently, optimization control in batch processes is crucial in order to derive the maximum benefit. In this paper, a run-to-run product quality control based on iterative learning optimization control is developed. Moreover, a rigorous theorem is proposed and proven in this paper, which states that the tracking error under the optimal iterative learning control （ILC） law can converge to zero. In this paper, a typical nonlinear batch continuous stirred tank reactor （CSTR） is considered, and the results show that the performance of trajectory tracking is gradually improved by the ILC.

Predictive Sliding Mode Control to a Thermal Process for Batch Dyeing

The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.

Automatic Synthesis of Batch Process Operating Procedures

A three-step synthesis strategy for the automatic synthesis of operating procedures in batch processoperations is presented in this paper.The first step is pre-operation which consists of a set of checks that mustbe considered before starting the basic process operation.The second step is operation which is described by a setof basic control instructions.The third step is post-operation described by a set of instructions that must becarried out when the basic process operation is terminated.The three-step synthesis method has been imple-mented as part of a prototype recipe management system.

Learning control of fermentation process with an improved DHP algorithm

Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.

Monitoring Saccharification Process in Brewery Industry Using Quality Control Charts

The aim of this study was to establish a control system for saccharification process using quality control charts. To achieve this goal, temperature, pH and brix were measured at 12 minutes intervals for 15 consecutive batches which took 2 hours each. The time variations for three process parameters were assessed to establish a good understanding of the saccharification process. The temperature varied between 58℃ and 62℃ while the pH decreased slowly due to oxidation, values of which varied between 5.7 and 5.0. Brix values increased linearly with time. The initial and final values of the three parameters varied from one batch to another. Of the three parameters, brix was not well represented on the quality control charts due to wide difference between initial and final values during saccharification. The final brix values varied between batches, from 10.6% to 11.6%. The control charts used in this study were X-bar and Range charts. The rules for interpreting control charts were implemented for both X-bar and R charts, results of which showed that the process was out of control, although some rules were not violated due to little number of batches studied. The values of for temperature and pH data (2.27℃ and 0.35, respectively) were lower compared to brix data (11.2%). The corresponding values of span between control limits, SPx and SPR for temperature and pH were also comparatively lower than those established from brix data. Due to larger values of for brix measurements, the corresponding control charts for brix were insensitive in identifying out-of-control points during saccharification process.

批产软件的研制流程和质量保证方法

在目前国内外承研业务发展和竞争形势下,越来越多的单机产品打破了零星或单件制造的生产模式,走上了产品化、批量化生产的道路。因此,软件的研制也需要从先前耗费大量人力与时间成本的模式转型为高效批量的模式。基于日常批产软件开发过程中的研制经验,文章介绍了批产软件概念、研制要求和流程、配置管理等,分析了批产软件研制过程中的流程和质量保证方法,提出了一些操作建议,旨在助推批产软件研制和质量保证工作的优化。

疫苗类批签发检验流程中的风险点控制分析

目的:在疫苗类批签发实验室建立风险点控制,保证最终检验数据和结果准确、合规。方法:依据批签发检验流程中各个环节及涉及的因素,结合实验室一线的实践操作,通过监督检查的方式,发现风险点,从而提出风险点的控制措施。结果与结论:随着批签发机构的扩容和批签发品种目录的扩大,批签发检验中的风险也随之增加。本文总结了疫苗类批签发检验流程中的风险点控制,为同行提供参考,保证上市的疫苗质量,助力我国疫苗产品在国际社会发挥更大的作用。

面向飞机装配批架次完工时间的仿真预测方法

针对传统离散事件仿真方法缺乏对产品间差异化分析的局限性,提出一种面向飞机装配批架次作业过程的仿真预测方法。围绕飞机架次标签,研究对批架次装配作业过程中各类基本要素与交互关系的形式化定义,由此完成站位、整线仿真模型的构建;研究支持产品差异化分析的仿真推进框架与执行机制;以仿真结果数据为基础,提出基于区间估计法的架次完工时间预测方法。实验结果表明:该方法能准确地输出各架次预计完工时间的置信区间,为现场提供可靠的评估依据。

GNSS接收机原始数据批量转换为RINEX文件方法研究

在铁路线路工程平面控制网卫星定位测量中,需要将大量GNSS接收机原始观测数据转换为与接收机无关的RINEX格式文件,以天宝GNSS接收机观测数据为研究对象,采用C#语言对该公司提供的GNSS接收机原始观测数据解码程序Convert To RINEX进行二次开发,分析该程序的批处理文件语法规则,然后基于批处理文件调用Convert To RINEX程序的方式,编制天宝GNSS观测数据批处理程序。工程实践表明,该批处理器软件能够方便快捷地将海量原始数据批量转换为RINEX格式文件,极大地节约卫星定位测量数据处理工程中数据预处理所需时间,显著提高了生产效率。

一种间歇测量下产品质量轨迹跟踪控制方法

在间歇过程中,传统工艺缺少产品质量的在线传感器,因此很难直接跟踪产品质量轨迹。基于过程变量与产品质量之间的偏最小二乘(PLS)模型,提出一种间歇测量下产品质量轨迹跟踪控制方法。在批内设定时间窗口,首先利用缺失数据算法估计未知的过程变量,再根据过程变量预测产品质量,并采用迭代学习控制和模型预测控制(MPC)相结合的方法设计控制器,达到跟踪当前批次产品质量设定点的目的。该方法采用移动窗口实现MPC的滚动优化,克服了批间和批内的干扰,从而使输出轨迹能精确跟踪期望轨迹。最后,在连续搅拌反应釜(CSTR)上进行仿真研究,仿真结果说明了该方法的有效性。

基于动态时间规整的制丝批次间差异评价方法

在卷烟制丝生产中,通常采用统计过程控制的方法评价生产过程质量,由于其基于稳态性的假设,忽略料头与料尾的数据,该研究使用生产全过程数据针对不同批次之间的质量差异如何评价的问题,提出一种基于动态时间规整(DTW)的批次间差异评价方法。首先,介绍烟草加工批次间差异的成因及其评价的意义;然后,对异常检测相关理论进行综述,分析统计模型、聚类、神经网络等方法在批次生产场景下的局限性,指出弹性相似度测量在变速时间序列比较中的优势;随后,详细介绍DTW算法原理,并将其推广到处理多变量时间序列数据的场景。在此基础上,设计一种利用DTW距离来评价不同加工批次与优质批次差异的框架。最后,以卷烟生产中的松散回潮工序为例,应用所提方法对100个批次进行差异性评估并进行可视化,验证该方法的有效性,进一步结合统计过程控制来说明可能的应用场景。该研究可为烟草制丝质量控制提供一种数据驱动的新思路,存在扩展至其他流程生产过程的可能性。

Optimal iterative learning control for end-point product qualities in semi-batch process based on neural network model

An optimal iterative learning control （ILC） strategy of improving endpoint products in semi-batch processes is presented by combining a neural network model. Control affine feed-forward neural network （CAFNN） is proposed to build a model of semi-batch process. The main advantage of CAFNN is to obtain analytically its gradient of endpoint products with respect to input. Therefore, an optimal ILC law with direct error feedback is obtained explicitly, and the convergence of tracking error can be analyzed theoretically. It has been proved that the tracking errors may converge to small values. The proposed modeling and control strategy is illustrated on a simulated isothermal semi-batch reactor, and the results show that the endpoint products can be improved gradually from batch to batch.

小批量多品种模式下SPC监控系统的设计与运用

文章以铁路交通行业某小批量多品种产品加工工厂为研究对象。在收集实际生产过程数据的基础上,分析统计过程控制(Statistical Process Control,SPC)监控系统的结构与功能,建立了适用于小批量多品种产品的SPC监控系统,并将其运用于实际生产过程。结果表明,在小批量多品种的生产模式下可以进行SPC实时监控分析,对生产过程中可能存在的异常提出预警,从而提升生产过程的稳定性。

Guaranteed Cost Iterative Learning Control for Multi-Phase Batch Processes

Batch process is a typical multi-phase process. Due to the interaction between the phases of the batch process, high precision control in a single phase cannot guarantee high precision control of the whole batch process. In order to solve this problem, the guaranteed cost iterative learning control(ILC) of multi-phase batch processes is studied in this paper. Firstly, through introducing the output error, the state error and the extended information, the multi-phase batch process is transformed into an equivalent 2D switched system which has different dimensions. In addition, under the measurable condition, the guaranteed cost iterative learning control law with extended information is designed. The proposed control law ensures not only the stability of the system but also the optimal control performance. Next, in order to study the stability of the system and the minimum running time under the condition of stable running, the multi-Lyapunov function method is used. By means of the average dwell time method, the sufficient conditions ensuring system to be exponentially stable are given in the form of linear matrix inequality(LMI). Finally, the injection molding process is taken as an example to make simulation, which shows the feasibility and effectiveness of the proposed method.

试车振动数据FFT批处理算法

本文梳理了姿轨控发动机点火试车振动数据频域处理过程,针对在频谱分析软件中处理振动数据存在较多人工操作步骤,设计开发振动数据FFT批处理算法。经算法验证,结果证明其可行有效,提高数据交付的快速准确性。

尺寸链在批量车身尺寸精度控制中的应用

如何对汽车车身尺寸精度进行精准控制和问题精准解决,是一项比较复杂的系统工程,也是提升汽车竞争力的根本。本文主要把尺寸链应用到批量车身尺寸精度控制中,提出了尺寸系数、计算公差带、CS置信度概念,通过尺寸链计算得出在现有条件下的尺寸要素控制标准,通过数字化手段实时监控,实现车身尺寸精准控制及问题解决。

过程分析技术的理念与发展

过程分析技术(PAT)是新世纪以来过程工业的重要技术进展.研究简要介绍了过程分析在过程分析化学、过程分析技术中概念的转化,概述了PAT的发展.通过阐述PAT的架构和理念,说明了过程分析技术与计算机集成过程系统的对应关系,同时对技术发展的前景和遇到的问题进行了探讨,展望了过程分析技术的发展对过程工程和控制理论的促进作用.

间歇过程动态优化方法综述

间歇过程的动态优化近年来引起了广泛关注.针对近期主要的研究成果,综述了间歇过程动态优化中的数学模型、求解方法及控制架构等问题,介绍了间歇过程目前主要的操作优化方法,具体分析了含不确定性间歇过程的动态优化策略,总结了间歇过程常用的优化模拟计算工具.最后探讨了这一领域中值得进一步研究的问题和可能的发展方向.