902 resultados para Intelligent control systems
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Continuous loading and unloading can cause breakdown of cranes. In seeking solution to this problem, the use of an intelligent control system for improving the fatigue life of cranes in the control of mechatronics has been under study since 1994. This research focuses on the use of neural networks as possibilities of developing algorithm to map stresses on a crane. The intelligent algorithm was designed to be a part of the system of a crane, the design process started with solid works, ANSYS and co-simulation using MSc Adams software which was incorporated in MATLAB-Simulink and finally MATLAB neural network (NN) for the optimization process. The flexibility of the boom accounted for the accuracy of the maximum stress results in the ADAMS model. The flexibility created in ANSYS produced more accurate results compared to the flexibility model in ADAMS/View using discrete link. The compatibility between.ADAMS and ANSYS softwares was paramount in the efficiency and the accuracy of the results. Von Mises stresses analysis was more suitable for this thesis work because the hydraulic boom was made from construction steel FE-510 of steel grade S355 with yield strength of 355MPa. Von Mises theory was good for further analysis due to ductility of the material and the repeated tensile and shear loading. Neural network predictions for the maximum stresses were then compared with the co-simulation results for accuracy, and the comparison showed that the results obtained from neural network model were sufficiently accurate in predicting the maximum stresses on the boom than co-simulation.
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Several studies have reported impairment in cardiovascular function and control in diabetes. The studies cited in this review were carried out from a few days up to 3 months after streptozotocin administration and were concerned with the control of the circulation. We observed that early changes (5 days) in blood pressure control by different peripheral receptors were maintained for several months. Moreover, the impairment of reflex responses observed after baroreceptor and chemoreceptor stimulation was probably related to changes in the efferent limb of the reflex arc (sympathetic and parasympathetic), but changes also in the central nervous system could not be excluded. Changes in renal sympathetic nerve activity during volume expansion were blunted in streptozotocin-treated rats, indicating an adaptive natriuretic and diuretic response in the diabetic state. The improvement of diabetic cardiovascular dysfunction induced by exercise training seems to be related to changes in the autonomic nervous system. Complementary studies about the complex interaction between circulation control systems are clearly needed to adequately address the management of pathophysiological changes associated with diabetes.
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Due to various advantages such as flexibility, scalability and updatability, software intensive systems are increasingly embedded in everyday life. The constantly growing number of functions executed by these systems requires a high level of performance from the underlying platform. The main approach to incrementing performance has been the increase of operating frequency of a chip. However, this has led to the problem of power dissipation, which has shifted the focus of research to parallel and distributed computing. Parallel many-core platforms can provide the required level of computational power along with low power consumption. On the one hand, this enables parallel execution of highly intensive applications. With their computational power, these platforms are likely to be used in various application domains: from home use electronics (e.g., video processing) to complex critical control systems. On the other hand, the utilization of the resources has to be efficient in terms of performance and power consumption. However, the high level of on-chip integration results in the increase of the probability of various faults and creation of hotspots leading to thermal problems. Additionally, radiation, which is frequent in space but becomes an issue also at the ground level, can cause transient faults. This can eventually induce a faulty execution of applications. Therefore, it is crucial to develop methods that enable efficient as well as resilient execution of applications. The main objective of the thesis is to propose an approach to design agentbased systems for many-core platforms in a rigorous manner. When designing such a system, we explore and integrate various dynamic reconfiguration mechanisms into agents functionality. The use of these mechanisms enhances resilience of the underlying platform whilst maintaining performance at an acceptable level. The design of the system proceeds according to a formal refinement approach which allows us to ensure correct behaviour of the system with respect to postulated properties. To enable analysis of the proposed system in terms of area overhead as well as performance, we explore an approach, where the developed rigorous models are transformed into a high-level implementation language. Specifically, we investigate methods for deriving fault-free implementations from these models into, e.g., a hardware description language, namely VHDL.
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Efficient production and consumption of energy has become the top priority of national and international policies around the world. Manufacturing industries have to address the requirements of the government in relation to energy saving and ecologically sustainable products. These industries are also concerned with energy and material usage due to their rising costs. Therefore industries have to find solutions that can support environmental preservation yet maintain competitiveness in the market. Welding, a major manufacturing process, consumes a great deal of material and energy. It is a crucial process in improving a products life-cycle cost, strength, quality and reliability. Factors which lead to weld related inefficiencies have to be effectively managed, if industries are to meet their quality requirements and fulfil a high-volume production demand. Therefore it is important to consider some practical strategies in welding process for optimization of energy and material consumption. The main objective of this thesis is to explore the methods of minimizing the ecological footprint of the welding process and methods to effectively manage its material and energy usage in the welding process. The author has performed a critical review of the factors including improved weld power source efficiency, efficient weld techniques, newly developed weld materials, intelligent welding systems, weld safety measures and personnel training. The study lends strong support to the fact that the use of eco-friendly welding units and the quality weld joints obtained with minimum possible consumption of energy and materials should be the main directions of improvement in welding systems. The study concludes that, gradually implementing the practical strategies mentioned in this thesis would help the manufacturing industries to achieve on the following - reduced power consumption, enhanced power control and manipulation, increased deposition rate, reduced cycle time, reduced joint preparation time, reduced heat affected zones, reduced repair rates, improved joint properties, reduced post-weld operations, improved automation, improved sensing and control, avoiding hazardous conditions and reduced exposure of welder to potential hazards. These improvement can help in promotion of welding as a green manufacturing process.
Effet des actions pdagogiques sur l'tat motionnel de l'apprenant dans un systme tutoriel intelligent
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Mmoire numris par la Division de la gestion de documents et des archives de l'Universit de Montral
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Cette thse vise dfinir une nouvelle mthode denseignement pour les systmes tutoriels intelligents dans le but damliorer lacquisition des connaissances. Lapprentissage est un phnomne complexe faisant intervenir des mcanismes motionnels et cognitifs de nature consciente et inconsciente. Nous nous intressons mieux comprendre les mcanismes inconscients du raisonnement lors de lacquisition des connaissances. Limportance de ces processus inconscients pour le raisonnement est bien documente en neurosciences, mais demeure encore largement inexplore dans notre domaine de recherche. Dans cette thse, nous proposons la mise en place dune nouvelle approche pdagogique dans le domaine de lducation implmentant une taxonomie neuroscientifique de la perception humaine. Nous montrons que cette nouvelle approche agit sur le raisonnement et, tour de rle, amliore lapprentissage gnral et linduction de la connaissance dans un environnement de rsolution de problme. Dans une premire partie, nous prsentons limplmentation de notre nouvelle mthode dans un systme tutoriel visant amliorer le raisonnement pour un meilleur apprentissage. De plus, compte tenu de limportance des mcanismes motionnels dans lapprentissage, nous avons galement procd dans cette partie la mesure des motions par des capteurs physiologiques. Lefficacit de notre mthode pour lapprentissage et son impact positif observ sur les motions a t valide sur trente et un participants. Dans une seconde partie, nous allons plus loin dans notre recherche en adaptant notre mthode visant amliorer le raisonnement pour une meilleure induction de la connaissance. Linduction est un type de raisonnement qui permet de construire des rgles gnrales partir dexemples spcifiques ou de faits particuliers. Afin de mieux comprendre limpact de notre mthode sur les processus cognitifs impliqus dans ce type de raisonnement, nous avons eu recours des capteurs crbraux pour mesurer lactivit du cerveau des utilisateurs. La validation de notre approche ralise sur quarante-trois volontaires montre lefficacit de notre mthode pour linduction de la connaissance et la viabilit de mesurer le raisonnement par des mesures crbrales suite lapplication approprie dalgorithmes de traitement de signal. Suite ces deux parties, nous clorons la thse par une discussion applicative en dcrivant la mise en place dun nouveau systme tutoriel intelligent intgrant les rsultats de nos travaux.
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Shrimp grow out systems under zero water exchange mode demand constant remediation of total ammonia nitrogen (TAN) andNO2 Nto protect the crop. To address this issue, aninexpensive and user-friendly technology using immobilized nitrifying bacterial consortia (NBC) as bioaugmentors has been developed and proposed for adoption in shrimp culture systems. Indigenous NBC stored at 4 C were activated at room temperature (28 C) and cultured in a 2 L bench top fermentor. The consortia, after enumeration by epifluorescence microscopy,were immobilized on delignifiedwood particles of a soft wood tree Ailantus altissima (3001500 m) having a surface area of 1.87m2 g1. Selection of wood particle as substratumwas based on adsorption of NBC on to the particles, biofilm formation, and their subsequent nitrification potential. The immobilization could be achievedwithin 72 h with an initial cell density of 1105 cells mL1. On experimenting with the lowest dosage of 0.2 g (wet weight) immobilized NBC in 20 L seawater, a TAN removal rate of 2.4 mg L1 within three days was observed. An NBC immobilization device could be developed for on site generation of the bioaugmentor preparation as per requirement. The product of immobilization never exhibited lag phase when transferred to fresh medium. The extent of nitrification in a simulated systemwas two times the rate observed in the control systems suggesting the efficacy in real life situations. The products of nitrification in all experiments were undetectable due to denitrifying potency, whichmade the NBC an ideal option for biological nitrogen removal. The immobilized NBC thus generated has been named TANOX (Total Ammonia Nitrogen Oxidizer)
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Fujaba is an Open Source UML CASE tool project started at the software engineering group of Paderborn University in 1997. In 2002 Fujaba has been redesigned and became the Fujaba Tool Suite with a plug-in architecture allowing developers to add functionality easily while retaining full control over their contributions. Multiple Application Domains Fujaba followed the model-driven development philosophy right from its beginning in 1997. At the early days, Fujaba had a special focus on code generation from UML diagrams resulting in a visual programming language with a special emphasis on object structure manipulating rules. Today, at least six rather independent tool versions are under development in Paderborn, Kassel, and Darmstadt for supporting (1) reengineering, (2) embedded real-time systems, (3) education, (4) specification of distributed control systems, (5) integration with the ECLIPSE platform, and (6) MOF-based integration of system (re-) engineering tools. International Community According to our knowledge, quite a number of research groups have also chosen Fujaba as a platform for UML and MDA related research activities. In addition, quite a number of Fujaba users send requests for more functionality and extensions. Therefore, the 8th International Fujaba Days aimed at bringing together Fujaba develop- ers and Fujaba users from all over the world to present their ideas and projects and to discuss them with each other and with the Fujaba core development team.
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Aquest projecte pretn presentar de forma clara i detallada lestructura i el funcionament del robot aix com dels components que el conformen. Aquesta informaci s de vital importncia a lhora de desenvolupar aplicacions per al robot. Un cop descrites les caracterstiques del robot sanalitzaran les eines necessries i/o disponibles per poder desenvolupar programari per cada nivell de la forma ms senzilla i eficient possible. Posteriorment sanalitzaran els diferents nivells de programaci i sen contrastaran els avantatges i els inconvenients de cada un. Aquest anlisi es comenar fent pel nivell ms alt i anir baixant amb la intenci de no entrar en nivells ms baixos del necessari. Baixar un nivell en la programaci suposa haver de crear aplicacions sempre compatibles amb els nivells superiors de forma que com ms es baixa ms augmenta la complexitat. A partir daquest anlisi sha arribat a la conclusi que per tal daprofitar totes les prestacions del robot s precs arribar a programar en el nivell ms baix del robot. Finalment lobjectiu s obtenir una srie de programes per cada nivell que permetin controlar el robot i fer-lo seguir senzilles trajectries
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Aquest projecte saplica sobre el robot PRIM (Plataforma Robotitzada dInformaci Multimdia), un robot autnom no humanoide creat el 2004 per Ateneu Informtic (AI) que permet realitzar trajectries 2D grcies a un sistema de tracci format per dues rodes motrius propulsades independentment. La plataforma PRIM s controlada a partir del control predictiu, aquest control es va implementar en un projecte anterior, creat per lAlexandre Blasco Gutierrez i titulat Implementaci de tcniques MPC (Model Predictiu Control) sobre la plataforma PRIM I. El que es pretn en aquest projecte s millorar els resultats obtinguts en el passat projecte reformulant la llei de control i analitzar les discrepncies obtingudes en les metodologies que sutilitzen per minimitzar la funci de costos a partir de simulacions de trajectries
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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task
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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system
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This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields
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This paper presents the design and implementation of a mission control system (MCS) for an autonomous underwater vehicle (AUV) based on Petri nets. In the proposed approach the Petri nets are used to specify as well as to execute the desired autonomous vehicle mission. The mission is easily described using an imperative programming language called mission control language (MCL) that formally describes the mission execution thread. A mission control language compiler (MCL-C) able to automatically translate the MCL into a Petri net is described and a real-time Petri net player that allows to execute the resulting Petri net onboard an AUV are also presented
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In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach
