882 resultados para Process control applications


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This paper describes a new statistical, model-based approach to building a contact state observer. The observer uses measurements of the contact force and position, and prior information about the task encoded in a graph, to determine the current location of the robot in the task configuration space. Each node represents what the measurements will look like in a small region of configuration space by storing a predictive, statistical, measurement model. This approach assumes that the measurements are statistically block independent conditioned on knowledge of the model, which is a fairly good model of the actual process. Arcs in the graph represent possible transitions between models. Beam Viterbi search is used to match measurement history against possible paths through the model graph in order to estimate the most likely path for the robot. The resulting approach provides a new decision process that can be use as an observer for event driven manipulation programming. The decision procedure is significantly more robust than simple threshold decisions because the measurement history is used to make decisions. The approach can be used to enhance the capabilities of autonomous assembly machines and in quality control applications.

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A promising technique for the large-scale manufacture of micro-fluidic devices and photonic devices is hot embossing of polymers such as PMMA. Micro-embossing is a deformation process where the workpiece material is heated to permit easier material flow and then forced over a planar patterned tool. While there has been considerable, attention paid to process feasibility very little effort has been put into production issues such as process capability and eventual process control. In this paper, we present initial studies aimed at identifying the origins and magnitude of variability for embossing features at the micron scale in PMMA. Test parts with features ranging from 3.5- 630 µm wide and 0.9 µm deep were formed. Measurements at this scale proved very difficult, and only atomic force microscopy was able to provide resolution sufficient to identify process variations. It was found that standard deviations of widths at the 3-4 µm scale were on the order of 0.5 µm leading to a coefficient of variation as high as 13%. Clearly, the transition from test to manufacturing for this process will require understanding the causes of this variation and devising control methods to minimize its magnitude over all types of parts.

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One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

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Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

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Process supervision is the activity focused on monitoring the process operation in order to deduce conditions to maintain the normality including when faults are present Depending on the number/distribution/heterogeneity of variables, behaviour situations, sub-processes, etc. from processes, human operators and engineers do not easily manipulate the information. This leads to the necessity of automation of supervision activities. Nevertheless, the difficulty to deal with the information complicates the design and development of software applications. We present an approach called "integrated supervision systems". It proposes multiple supervisors coordination to supervise multiple sub-processes whose interactions permit one to supervise the global process

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Expert supervision systems are software applications specially designed to automate process monitoring. The goal is to reduce the dependency on human operators to assure the correct operation of a process including faulty situations. Construction of this kind of application involves an important task of design and development in order to represent and to manipulate process data and behaviour at different degrees of abstraction for interfacing with data acquisition systems connected to the process. This is an open problem that becomes more complex with the number of variables, parameters and relations to account for the complexity of the process. Multiple specialised modules tuned to solve simpler tasks that operate under a co-ordination provide a solution. A modular architecture based on concepts of software agents, taking advantage of the integration of diverse knowledge-based techniques, is proposed for this purpose. The components (software agents, communication mechanisms and perception/action mechanisms) are based on ICa (Intelligent Control architecture), software middleware supporting the build-up of applications with software agent features

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This paper deals with the problem of semiactive vibration control of civil engineering structures subject to unknown external disturbances (for example, earthquakes, winds, etc.). Two kinds of semiactive controllers are proposed based on the backstepping control technique. The experimental setup used is a 6-story test structure equipped with shear-mode semiactive magnetorheological dampers being installed in the Washington University Structural Control and Earthquake Engineering Laboratory (WUSCEEL). The experimental results obtained have verified the effectiveness of the proposed control algorithms

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Las organizaciones en la actualidad deben encontrar diferentes maneras de sobrevivir en un tiempo de rápida transformación. Uno de los mecanismos usados por las empresas para adaptarse a los cambios organizacionales son los sistemas de control de gestión, que a su vez permiten a las organizaciones hacer un seguimiento a sus procesos, para que la adaptabilidad sea efectiva. Otra variable importante para la adaptación es el aprendizaje organizacional siendo el proceso mediante el cual las organizaciones se adaptan a los cambios del entorno, tanto interno como externo de la compañía. Dado lo anterior, este proyecto se basa en la extracción de documentación soporte valido, que permita explorar las interacciones entre estos dos campos, los sistemas de control de gestión y el aprendizaje organizacional, además, analizar el impacto de estas interacciones en la perdurabilidad organizacional. ​

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L’objecte del present treball és la realització d’una aplicació que permeti portar a terme el control estadístic multivariable en línia d’una planta SBR. Aquesta eina ha de permetre realitzar un anàlisi estadístic multivariable complet del lot en procés, de l’últim lot finalitzat i de la resta de lots processats a la planta. L’aplicació s’ha de realitzar en l’entorn LabVIEW. L’elecció d’aquest programa ve condicionada per l’actualització del mòdul de monitorització de la planta que s’està desenvolupant en aquest mateix entorn

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L'objectiu general d'aquest treball és trobar i mostrar una eina que permeti obtenir una representació dels senyals procedents de sistemes dinàmics adequada a les necessitats dels sistemes de Supervisió Experta de processos. Aquest objectiu general es pot subdividir en diverses parts, que són tractades en els diferents capítols que composen el treball i que es poden resumir en els següents punts: En primer lloc, cal conèixer les necessitats dels sistemes de Supervisió: La gran quantitat de dades que provenen dels processos fa necessari el tractament d'aquestes dades per obtenir-ne d'altres, més elaborades, amb un nivell més elevat de representació. La utilització de raonament qualitatiu, pròpia dels éssers humans, comporta la necessitat de representar simbòlicament els senyals, de traduir les dades numèriques en símbols. La Supervisió de sistemes dinàmics comporta que el temps sigui una variable fonamental, la asincronia dels esdeveniments significatius per a la Supervisió fa que les representacions més adequades i útils dels senyals siguin asíncrones. Finalment,l'ús dels coneixements experimentals en la Supervisió dels processos comporta que les representacions més naturals siguin les més útils. Aquestes necessitats fan de la representació dels senyals mitjançant episodis l'eina amb més possibilitats per assolir els objectius que es volen assolir. Per això, es presenta un formalisme que permet descriure i incloure-hi la formalització i les diferents aproximacions a aquest tipus de representació ja existents i, al mateix temps, augmentar-ne la significació a través de característiques dels senyals que no es tenen en compte en les aproximacions ja existents. El següent pas és aprofitar el nou formalisme per obtenir una nova representació amb un grau més gran de significació, cosa que s'aconsegueix representant explícitament les discontinuïtats i els períodes estacionaris o d'estabilitat, molt significatius en Supervisió de processos. Un problema sempre present en el tractament de senyals és el soroll que els afecta. Per aquest motiu es presenta un mètode que permet filtrar el soroll de manera que les representacions resultants quedin afectades el mínim possible per aquest tractament. Finalment, es presenta l'aplicació en línia de les eines descrites. La representació en línia dels senyals comporta el tractament de la incertesa inherent al coneixement parcial del senyal (un episodi no pot ser determinat i caracteritzat completament fins que no s'acaba). L'obtenció de resultats amb determinats graus de certesa és perfectament coherent amb la seva utilització posterior mitjançant Sistemes Experts o altres eines de la IA. Totes les aportacions del treball vénen acompanyades d'exemples i/o aplicacions que permeten observar-ne la utilitat i les limitacions.

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This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.

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The relationship between minimum variance and minimum expected quadratic loss feedback controllers for linear univariate discrete-time stochastic systems is reviewed by taking the approach used by Caines. It is shown how the two methods can be regarded as providing identical control actions as long as a noise-free measurement state-space model is employed.

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Control systems theory can be a discipline difficult to learn without some laboratory help. With the help of focused laboratories this discipline turns to be very interesting to the students involved. The main problem is that laboratories aren't always available to students, and sometimes, when they are available, aren't big enough to a growing student population. Thus, with computer networks growing so fast, why don't create remote control labs that can be used by a large number of students? Why don't create remote control labs using Internetⓒ Copyright ?2001 IFAC Keywords: Remote Control, Computer Networks, Database, Educational Aids, Laboratory Education, Communication Control Applications.

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