Plantwide Optimizing Control of a continuous bioethanol production process

In this work, the Plantwide Control (PWC) problem of a continuous bioethanol process is investigated from a Plantwide Optimizing Control (PWOC) perspective. PWOC addresses the plantwide control problem integrating real-time optimization and control for optimal operation. Two different PWOC approaches have been considered: a single-layer direct optimizing control approach (one-layer) and a multi-layer without coordination approach (two-layer). The performance of these two PWOC schemes is compared with more conventional decentralized architectures, demonstrating the benefits of using plantwide optimization-based control strategies in the bioethanol process, towards reaching maximum profitability.     

射频/微波功率测量不确定度分析及计算

本文根据戴维宁等效电路,建立了射频,微波功率传输信号流图,阐述了功率测量电路中相关测量参数及其相互关系,并分析了测量不确定度的来源及改善失配误差的方法,最后介绍了常见的三种测量不确定合成方法:最大误差不确定度、RSS误差不确定度和扩展不确定度.     

Control of robust design in multiobjective optimization under uncertainties

In design and optimization problems, a solution is called robust if it is stable enough with respect to perturbation of model input parameters. In engineering design optimization, the designer may prefer a use of robust solution to a more optimal one to set a stable system design. Although in literature there is a handful of methods for obtaining such solutions, they do not provide a designer with a direct and systematic control over a required robustness. In this paper, a new approach to robust design in multiobjective optimization is introduced, which is able to generate robust design with model uncertainties. In addition, it introduces an opportunity to control the extent of robustness by designer preferences. The presented method is different from its other counterparts. For keeping robust design feasible, it does not change any constraint. Conversely, only a special tunable objective function is constructed to incorporate the preferences of the designer related to the robustness. The effectiveness of the method is tested on well known engineering design problems.     

Performance evaluation of collaboration in the design process: Using interoperability measurement

A design process, whether for a product or for a service, is composed of a large number of activities connected by data and information exchanges. The quality of these exchanges, called in this paper collaboration, requires the ability to exchange useful, understandable and unambiguous data and information to the different designers involved. In this paper, a global framework is first set for process/product performance management. Then, the research question focuses on the definition and evaluation of the performance of collaborations, and by extension, of the design process in its entirety. This performance evaluation requires the definition of several key elements such as object to evaluate, the performance criteria, indicators and action variables. In order to define the object of evaluation, this paper relies on a literature study on collaboration resulting in an ECORE meta-model of collaborative processes. The collaboration performance measurement is for its part based on the concept of interoperability. This measure estimates the technical and conceptual interoperability of the different pairwise collaborations. The paper is concluded by proposing a tooled methodology for collaborations’ performance evaluation including two main phases: process modeling and interoperability measurement. Tooling is provided through the Eclipse Modeling Framework (EMF) using its (meta-) model edition, constraint validation and model comparison features. The applicability of the methodology is also illustrated using a case study in design.     

板式吸收塔优化设计研究与软件开发

以板式吸收塔系统的年总费用为目标函数，建立了优化设计数学模型，以吸收塔的液气比为决策变量，用单变量优化算法(菲波拿契法)求得最优解。用Visual Basic6．0开发出板式吸收塔优化设计软件。软件运行于Windows 9x系统，界面友好，操作方便。算列表明优化设计比常规设计节省生产成本。     

填料吸收塔多媒体课程设计系统软件

以Visual Basic6．0和3Dmax为工具,开发了填料吸收塔多媒体课程设计系统软件。软件界面简洁友好、使用灵活方便、运行稳定安全。该软件提供了多个典型的气液混合物系统和不同的计算方法,既可用于不同层次学生进行课程设计或毕业设计,又便于教师对学生的计算过程及计算结果进行检查和评价,极大地丰富了教学内容,产生了传统方式无法比拟的效果。     

Multivariable control of ill-conditioned distillation columns utilizing process knowledge

In distillation, a reliable model of the column is generally considered as a prerequisite for the design of efficient two-product control by multivariable methods. However, such models are often very hard to obtain. In fact, even very small identification errors may introduce features which are in conflict with physical knowledge, and which make the model useless. Instead of focusing on the development of consistent models, this work is concerned with the utilization of physical process knowledge directly for multivariable control, even if a reliable input-output model is lacking. Such knowledge is, for example, the sign of the RGA-values and an estimate of the input-directionality. It is shown that such structural information of the process can form an entity of control-relevant knowledge that is sufficiently rich for the design of a multivariable SVD controller.     

Learning process in a class of computer integrated manufacturing systems with parametric uncertainties

The paper is concerned with a class of manufacturing processes described by a relational knowledge representation containing unknown parameters. Two kinds of the manufacturing processes with different structures of material and task flow are considered. For these kinds the algorithms of learning and control for the central decision support computer system integrating the manufacturing process are presented. The learning process consists in using the results of step by step knowledge validation and updating to the determination of the current control decisions. The idea of learning described in the paper may be considered as a generalization of the known concept of the adaptive control using the results of current identification. Simple illustrative examples, results of simulations for a simple case and additional remarks concerning related problems are included.     

Managing software process measurement: A metamodel-based approach

The evaluation of software processes is nowadays a very important issue due to the growing interest of software companies in the improvement of the productivity and quality of delivered products. Software measurement plays a fundamental role here. Given the great diversity of entities which are candidates for measurement in the software process improvement context (process models, projects, resources, products) this measurement must be performed in a consistent and integrated way. This will facilitate the making of decisions in process improvement. In this paper, a proposal for the integrated management of the software measurement is presented. The goal is to provide companies with a generic and flexible environment for software measurement which facilitates and establishes the basis for a common and effective measurement process and which is not restricted to only one kind of software entity or to a single quality or evaluation model. In order to achieve this, the proposal adopts the Model Driven Engineering philosophy and provides: a metamodel for the definition of software measurement models; a flexible method to measure any kind of software entity represented by its corresponding metamodel and GenMETRIC, which is the software tool that supports the framework.     

The measurement of team process

The construct validity of measures of team process was evaluated using predictive, known groups and multitrait-multimethod (MTMM) validation strategies. Military air crews (N = 51) flew two simulated missions. Independent judges provided evaluations of the same six team process variables in both scenarios. An MTMM analysis of judges' ratings treating judges as a method variable showed good convergent and discriminant validity. Judges' mean ratings of the six process variables were correlated with mission effectiveness. Some process measures discriminated between student and instructor teams, thus showing discrimination between known groups. Conversely, an MTMM analysis of ratings treating scenarios as a method showed poor convergent validity. We concluded that important team process behaviors have been identified and can be rated validly but that multiple observations are necessary to assess characteristics of individual teams with any accuracy. The discussion includes implications for practice and future research.     

Control of mobile robots with uncertainties in the dynamical model: a discrete time sliding mode approach with experimental results

In this note the trajectory tracking problem for a wheeled mobile base has been addressed, considering the presence of uncertainties in the dynamical model. The proposed solution is based on discrete sliding mode control, in order to ensure both robustness and implementability of the controller. The asymptotic boundedness of the tracking errors has been theoretically proved. The proposed discrete time algorithm has been experimentally tested, performing the experiments on the LABMATE vehicle available at the Robotics Lab of the University of Ancona, and compared with a kinematic controller proposed in the literature.     

Providing automated support for the GQM measurement process

Automating support for the Goals-Questions-Metrics (GQM) process can cut data collection costs by exploiting the data available in configuration management systems as well as the data supplied by code analysers. The author introduces a tool that is designed for this purpose and reviews its development and applications in industry     

A study on robust design optimization of layered plate bonding process considering uncertainties

Design optimization of layered plate bonding process is conducted by considering uncertainties in a manufacturing process, to reduce the crack failure arising due to the difference of thermal expansion coefficients of the adherents. Robust optimization is performed to minimize the mean and variance of the residual stress, which is the major cause of the failure, while constraining the distortion and the instantaneous maximum stress to the allowable limits. In this optimization, the dimension reduction (DR) method is employed to quantify the uncertainty of the responses in the bonding process. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. Response surface method (RSM) combined with sequential approximate optimization (SAO) technique is employed as an optimization tool. The obtained robust optimal solution is verified by the Monte Carlo simulation.     

高浓度吸收的计算机辅助计算

吸收是化工生产特别是石油化工生产中十分常见的过程,在化工原理教学中是一个典型的传质分离单元操作.针对复杂的高浓度吸收计算过程,本文利用MATLAB语言强大的方程求解、曲线拟合和数值积分功能,介绍计算机辅助求解方法的典型例题.结果表明,利用MATLAB解决化工原理工程计算问题快捷、准确和有效.     

Properties of multivariate process capability in the presence of gauge measurement errors and dependency measure of process variables

Nowadays process capability has been extensively studied as a mean of summarizing process performance relative to a set of specification limits. Most of the research papers related to process capability indices have assumed that there are no gauge measurement errors. Unfortunately, such an assumption does not reflect real situations accurately even with highly sophisticated advanced measuring instruments. In this paper, we study the behavior of multivariate process capability index (M_Cp$M{C}_p$) in the presence of gauge measurement errors. In addition, the effect of correlation coefficient and measurement capability on the statistical properties of the estimated M_Cp$M{C}_p$ are also studied. The results indicate that correlation coefficients of process variables will notability change the statistical behavior of the multivariate process capability in the presence of gauge measurement errors. With the adjusted confidence intervals and suitable estimation method the more accurate testing procedure for M_Cp$M{C}_p$ by considering different values of correlation coefficient is obtained.     

The measurement of information technology absorption into information handling processes in business

The need for a comparative measure of information technology absorption in business is discussed. Studies of various forms of technological change are reviewed in terms of three issues; the level of measurement used, the research techniques/methods used and the approaches to the measurement of technology absorption. The requisite properties for an assessment of information technology absorption within business are outlined. A framework for a structured interview schedule is proposed which could assess approaches to information handling at several levels of analysis (e.g. departments, sites, organizations, industries). A pilot factor analysis of the IT items within the schedule across a sample of businesses reveals a sensible three-factor structure of IT influence within information handling. This form of measure is shown to offer sufficient sensitivity to assess technological changes within organizations and be relatable to behavioural outcomes. The extent of changes in management roles is shown to be correlated with degree of IT change along the three dimensions identified. The needs for further research are discussed.     

A program for confidence interval calculations for a Poisson process with background including systematic uncertainties: POLE 1.0

A Fortran 77 routine has been developed to calculate confidence intervals with and without systematic uncertainties using a frequentist confidence interval construction with a Bayesian treatment of the systematic uncertainties. The routine can account for systematic uncertainties in the background prediction and signal/background efficiencies. The uncertainties may be separately parametrized by a Gauss, log-normal or flat probability density function (PDF), though since a Monte Carlo approach is chosen to perform the necessary integrals a generalization to other parameterizations is particularly simple. Full correlation between signal and background efficiency is optional. The ordering schemes for frequentist construction currently supported are the likelihood ratio ordering (also known as Feldman-Cousins) and Neyman ordering. Optionally, both schemes can be used with conditioning, meaning the probability density function is conditioned on the fact that the actual outcome of the background process can not have been larger than the number of observed events.

Program summary

Title of program: POLE version 1.0Catalogue identifier: ADTAProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADTAProgram available from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: NoneComputer for which the program is designed: DELL PC 1 GB 2.0 Ghz Pentium IVOperating system under which the program has been tested: RH Linux 7.2 Kernel 2.4.7-10Programming language used: Fortran 77Memory required to execute with typical data: ∼1.6 MbytesNo. of bytes in distributed program, including test data, etc.: 373745No. of lines in distributed program, including test data, etc.: 2700Distribution format: tar gzip fileKeywords: Confidence interval calculation, Systematic uncertaintiesNature of the physical problem: The problem is to calculate a frequentist confidence interval on the parameter of a Poisson process with known background in presence of systematic uncertainties in experimental parameters such as signal efficiency or background prediction.Method of solution: A PDF for the confidence interval construction is constructed by folding a Poisson density function with a parametrization describing the posterior PDF of the systematic uncertainties. The construction is then performed with this new PDF according to different ordering schemes. The convolution is performed using a Monte Carlo integration method, providing greatest possible flexibility with respect to the parametrization.Restriction on the complexity of the problem: No restrictions.Typical running time: for calculation of a single confidence interval with 1000 steps in signal hypothesis space the wall clock time on a DELL PC 1 GB 2.0 Ghz Pentium IV with 4 GB swap is ca. 500 seconds. The wall clock time scales roughly linear with the number of steps in signal space.Unusual features of the program: POLE uses routines from the CERNLIB library [http://wwwasd.web.cern.ch/wwwasd/cernlib], which have to be linked in during compilation. It should be noted that the number of steps in signal space (maximal s required divided by the step-width) should not exceed 1000, since the corresponding arrays are predimensioned.References: [1] J. Conrad, O. Botner, A. Hallgren, C. Perez de los Heros, Including systematic uncertainties in confidence interval construction for Poisson statistics, Phys. Rev. D 67 (2003) 012002, hep-ex/0202013.