916 resultados para Adaptive control. Variable structure systems. Variable structure model-reference adaptive control
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La implantación de las tecnologías Internet ha permitido la extensión del uso de estrategias e-manufacturing y el desarrollo de herramientas para la recopilación, transformación y sincronización de datos de fabricación vía web. En este ámbito, un área de potencial desarrollo es la extensión del virtual manufacturing a los procesos de Performance Management (PM), área crítica para la toma de decisiones y ejecución de acciones de mejora en fabricación. Este trabajo doctoral propone un Arquitectura de Información para el desarrollo de herramientas virtuales en el ámbito PM. Su aplicación permite asegurar la interoperabilidad necesaria en los procesos de tratamiento de información de toma de decisión. Está formado por tres sub-sistemas: un modelo conceptual, un modelo de objetos y un marco Web compuesto de una plataforma de información y una arquitectura de servicios Web (WS). El modelo conceptual y el modelo de objetos se basa en el desarrollo de toda la información que se necesita para definir y obtener los diferentes indicadores de medida que requieren los procesos PM. La plataforma de información hace uso de las tecnologías XML y B2MML para estructurar un nuevo conjunto de esquemas de mensajes de intercambio de medición de rendimiento (PMXML). Esta plataforma de información se complementa con una arquitectura de servicios web que hace uso de estos esquemas para integrar los procesos de codificación, decodificación, traducción y evaluación de los performance key indicators (KPI). Estos servicios realizan todas las transacciones que permiten transformar los datos origen en información inteligente usable en los procesos de toma de decisión. Un caso práctico de intercambio de datos en procesos de medición del área de mantenimiento de equipos es mostrado para verificar la utilidad de la arquitectura. ABSTRAC The implementation of Internet technologies has led to e-Manufacturing technologies becoming more widely used and to the development of tools for compiling, transforming and synchronizing manufacturing data through the Web. In this context, a potential area for development is the extension of virtual manufacturing to Performance Measurement (PM) processes, a critical area for decision-making and implementing improvement actions in manufacturing. This thesis proposes a Information Architecture to integrate decision support systems in e-manufacturing. Specifically, the proposed architecture offers a homogeneous PM information exchange model that can be applied trough decision support in emanufacturing environment. Its application improves the necessary interoperability in decision-making data processing tasks. It comprises three sub-systems: a data model, a object model and Web Framework which is composed by a PM information platform and PM-Web services architecture. . The data model and the object model are based on developing all the information required to define and acquire the different indicators required by PM processes. The PM information platform uses XML and B2MML technologies to structure a new set of performance measurement exchange message schemas (PM-XML). This PM information platform is complemented by a PM-Web Services architecture that uses these schemas to integrate the coding, decoding, translation and assessment processes of the key performance indicators (KPIs). These services perform all the transactions that enable the source data to be transformed into smart data that can be used in the decision-making processes. A practical example of data exchange for measurement processes in the area of equipment maintenance is shown to demonstrate the utility of the architecture.
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Desde la aparición del turborreactor, el motor aeróbico con turbomaquinaria ha demostrado unas prestaciones excepcionales en los regímenes subsónico y supersónico bajo. No obstante, la operación a velocidades superiores requiere sistemas más complejos y pesados, lo cual ha imposibilitado la ejecución de estos conceptos. Los recientes avances tecnológicos, especialmente en materiales ligeros, han restablecido el interés por los motores de ciclo combinado. La simulación numérica de estos nuevos conceptos es esencial para estimar las prestaciones de la planta propulsiva, así como para abordar las dificultades de integración entre célula y motor durante las primeras etapas de diseño. Al mismo tiempo, la evaluación de estos extraordinarios motores requiere una metodología de análisis distinta. La tesis doctoral versa sobre el diseño y el análisis de los mencionados conceptos propulsivos mediante el modelado numérico y la simulación dinámica con herramientas de vanguardia. Las distintas arquitecturas presentadas por los ciclos combinados basados en sendos turborreactor y motor cohete, así como los diversos sistemas comprendidos en cada uno de ellos, hacen necesario establecer una referencia común para su evaluación. Es más, la tendencia actual hacia aeronaves "más eléctricas" requiere una nueva métrica para juzgar la aptitud de un proceso de generación de empuje en el que coexisten diversas formas de energía. A este respecto, la combinación del Primer y Segundo Principios define, en un marco de referencia absoluto, la calidad de la trasferencia de energía entre los diferentes sistemas. Esta idea, que se ha estado empleando desde hace mucho tiempo en el análisis de plantas de potencia terrestres, ha sido extendida para relacionar la misión de la aeronave con la ineficiencia de cada proceso involucrado en la generación de empuje. La metodología se ilustra mediante el estudio del motor de ciclo combinado variable de una aeronave para el crucero a Mach 5. El diseño de un acelerador de ciclo combinado basado en el turborreactor sirve para subrayar la importancia de la integración del motor y la célula. El diseño está limitado por la trayectoria ascensional y el espacio disponible en la aeronave de crucero supersónico. Posteriormente se calculan las prestaciones instaladas de la planta propulsiva en función de la velocidad y la altitud de vuelo y los parámetros de control del motor: relación de compresión, relación aire/combustible y área de garganta. ABSTRACT Since the advent of the turbojet, the air-breathing engine with rotating machinery has demonstrated exceptional performance in the subsonic and low supersonic regimes. However, the operation at higher speeds requires further system complexity and weight, which so far has impeded the realization of these concepts. Recent technology developments, especially in lightweight materials, have restored the interest towards combined-cycle engines. The numerical simulation of these new concepts is essential at the early design stages to compute a first estimate of the engine performance in addition to addressing airframe-engine integration issues. In parallel, a different analysis methodology is required to evaluate these unconventional engines. The doctoral thesis concerns the design and analysis of the aforementioned engine concepts by means of numerical modeling and dynamic simulation with state-of-the-art tools. A common reference is needed to evaluate the different architectures of the turbine and the rocket-based combined-cycle engines as well as the various systems within each one of them. Furthermore, the actual trend towards more electric aircraft necessitates a common metric to judge the suitability of a thrust generation process where different forms of energy coexist. In line with this, the combination of the First and the Second Laws yields the quality of the energy being transferred between the systems on an absolute reference frame. This idea, which has been since long applied to the analysis of on-ground power plants, was extended here to relate the aircraft mission with the inefficiency of every process related to the thrust generation. The methodology is illustrated with the study of a variable- combined-cycle engine for a Mach 5 cruise aircraft. The design of a turbine-based combined-cycle booster serves to highlight the importance of the engine-airframe integration. The design is constrained by the ascent trajectory and the allocated space in the supersonic cruise aircraft. The installed performance of the propulsive plant is then computed as a function of the flight speed and altitude and the engine control parameters: pressure ratio, air-to-fuel ratio and throat area.
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Robotics is an emerging field with great activity. Robotics is a field that presents several problems because it depends on a large number of disciplines, technologies, devices and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges. New uses are, for example, household robots or professional robots. To facilitate the low cost, rapid development of robotic systems, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems. Specifically, we model the decentralized activity and hormonal variation.
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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.
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Modern distribution is being shifted from paper-based, people-intensive marketing systems toward electronic-based procedures that rely on Internet communications and web-enhanced software tools. This article develops a typology of e-business technological innovations that have come to characterize cutting-edge distribution management. e-Business tools relevant to marketing channels are organized by the channel process flows that yield communication and transaction enhancements to distribution systems. Further, a model of the impact of e-business on channel performance is developed. The mediating role of channel structure on technology's impact on channel outcomes in terms of efficiency and effectiveness is also analyzed. Finally, implications of the e-business revolution for managers and researchers are discussed.
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We present a complex neural network model of user behavior in distributed systems. The model reflects both dynamical and statistical features of user behavior and consists of three components: on-line and off-line models and change detection module. On-line model reflects dynamical features by predicting user actions on the basis of previous ones. Off-line model is based on the analysis of statistical parameters of user behavior. In both cases neural networks are used to reveal uncharacteristic activity of users. Change detection module is intended for trends analysis in user behavior. The efficiency of complex model is verified on real data of users of Space Research Institute of NASU-NSAU.
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The value of knowing about data availability and system accessibility is analyzed through theoretical models of Information Economics. When a user places an inquiry for information, it is important for the user to learn whether the system is not accessible or the data is not available, rather than not have any response. In reality, various outcomes can be provided by the system: nothing will be displayed to the user (e.g., a traffic light that does not operate, a browser that keeps browsing, a telephone that does not answer); a random noise will be displayed (e.g., a traffic light that displays random signals, a browser that provides disorderly results, an automatic voice message that does not clarify the situation); a special signal indicating that the system is not operating (e.g., a blinking amber indicating that the traffic light is down, a browser responding that the site is unavailable, a voice message regretting to tell that the service is not available). This article develops a model to assess the value of the information for the user in such situations by employing the information structure model prevailing in Information Economics. Examples related to data accessibility in centralized and in distributed systems are provided for illustration.
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This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.
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This research is based on the premises that teams can be designed to optimize its performance, and appropriate team coordination is a significant factor to team outcome performance. Contingency theory argues that the effectiveness of a team depends on the right fit of the team design factors to the particular job at hand. Therefore, organizations need computational tools capable of predict the performance of different configurations of teams. This research created an agent-based model of teams called the Team Coordination Model (TCM). The TCM estimates the coordination load and performance of a team, based on its composition, coordination mechanisms, and job’s structural characteristics. The TCM can be used to determine the team’s design characteristics that most likely lead the team to achieve optimal performance. The TCM is implemented as an agent-based discrete-event simulation application built using JAVA and Cybele Pro agent architecture. The model implements the effect of individual team design factors on team processes, but the resulting performance emerges from the behavior of the agents. These team member agents use decision making, and explicit and implicit mechanisms to coordinate the job. The model validation included the comparison of the TCM’s results with statistics from a real team and with the results predicted by the team performance literature. An illustrative 26-1 fractional factorial experimental design demonstrates the application of the simulation model to the design of a team. The results from the ANOVA analysis have been used to recommend the combination of levels of the experimental factors that optimize the completion time for a team that runs sailboats races. This research main contribution to the team modeling literature is a model capable of simulating teams working on complex job environments. The TCM implements a stochastic job structure model capable of capturing some of the complexity not capture by current models. In a stochastic job structure, the tasks required to complete the job change during the team execution of the job. This research proposed three new types of dependencies between tasks required to model a job as a stochastic structure. These dependencies are conditional sequential, single-conditional sequential, and the merge dependencies.
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Personality has long been linked to performance. Evolutions in this relationship have brought forward new questions regarding the true nature of how personality impacts performance. Both direct and indirect relationships have been proven significant. This study further investigated potential indirect relationships by including a mediating variable, mental model formation, in the personality-performance relationship. Undergraduate students were assessed in a 6-week period, Time 1 - Time 2 experiment. Conceptualizations of personality included measures of the Big 5 model and Self-efficacy, with performance measured by content quiz and overall course scores. Findings showed that the Big 5 personality traits, extraversion and agreeableness, positively and significantly impacted commonality with the instructor's mental model. However, commonality with the instructor's mental model did not impact performance. In comparison, commonality with an expert mental model positively and significantly impacted performance for both the content quiz and overall course score. Furthermore, similarity with an expert mental model positively and significantly impacted overall course performance. Hypothesized full mediation of mental model formation for the personality-performance relationship was not supported due to a lack of direct effect relationships required for mediation. However, a revised conceptualization of results emerged. Findings from the current study point to the novel and unique role mental models play in the personality-performance relationship. While personality traits do impact mental model formation, accuracy in the mental models formed is critical to performance.
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Abstract Purpose – The purpose of this paper is to present a case study regarding the deployment of a previously developed model for the integration of management systems (MSs). The case study is developed at a manufacturing site of an international enterprise. The implementation of this model in a real business environment is aimed at assessing its feasibility. Design/methodology/approach – The presented case study takes into account different management systems standards (MSSs) progressively implemented, along the years, independently. The implementation of the model was supported by the results obtained from an investigation performed according to a structured diagnosis that was conducted to collect information related to the organizational situation of the enterprise. Findings – The main findings are as follows: a robust integrated management system (IMS), objectively more lean, structured and manageable was found to be feasible; this study provided an holistic view of the enterprise’s global management; clarifications of job descriptions and boundaries of action and responsibilities were achieved; greater efficiency in the use of resources was attained; more coordinated management of the three pillars of sustainability – environmental, economic and social, as well as risks, providing confidence and added value to the company and interested parties was achieved. Originality/value – This case study is pioneering in Portugal in respect to the implementation, at the level of an industrial organization, of the model previously developed for the integration of individualized MSs. The case study provides new insights regarding the implementation of IMSs including the rationalization of several resources and elimination of several types of organizational waste leveraging gains of efficiency. Due to its intrinsic characteristics, the model is able to support, progressively, new or revised MSSs according to the principles of annex SL (normative) – proposals for MSSs – of the International Organization for Standardization and the International Electrotechnical Commission, that the industrial organization can adopt beyond the current ones.
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Thesis (Ph.D.)--University of Washington, 2016-08
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Part 1: Introduction
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Personality has long been linked to performance. Evolutions in this relationship have brought forward new questions regarding the true nature of how personality impacts performance. Both direct and indirect relationships have been proven significant. This study further investigated potential indirect relationships by including a mediating variable, mental model formation, in the personality-performance relationship. Undergraduate students were assessed in a 6-week period, Time 1 - Time 2 experiment. Conceptualizations of personality included measures of the Big 5 model and Self-efficacy, with performance measured by content quiz and overall course scores. Findings showed that the Big 5 personality traits, extraversion and agreeableness, positively and significantly impacted commonality with the instructor’s mental model. However, commonality with the instructor’s mental model did not impact performance. In comparison, commonality with an expert mental model positively and significantly impacted performance for both the content quiz and overall course score. Furthermore, similarity with an expert mental model positively and significantly impacted overall course performance. Hypothesized full mediation of mental model formation for the personality-performance relationship was not supported due to a lack of direct effect relationships required for mediation. However, a revised conceptualization of results emerged. Findings from the current study point to the novel and unique role mental models play in the personality-performance relationship. While personality traits do impact mental model formation, accuracy in the mental models formed is critical to performance.
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This study analyzes the manifestation of the dimensions of Entrepreneurial Orientation (EO) and Project Management Systems (PMS). We used a qualitative approach to conduct exploratory research through a study in literature and a pilot case in a software company. Data was collected from semi structured interviews, documents, and records on file, then triangulated and treated with content analysis. The model proposed for the relationship between the types of PMS (ad hoc, Classic PM, innovation, entrepreneurship/intrapreneurship) and the dimensions of EO (innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy), was partially corroborated by empirical studies. New studies are suggested to validate the applicability and setup of the model.