22 resultados para modeling and prediction

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

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Vegeu el resum a l'inici del document de l'arxiu adjunt

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This paper presents a thermal modeling for power management of a new three-dimensional (3-D) thinned dies stacking process. Besides the high concentration of power dissipating sources, which is the direct consequence of the very interesting integration efficiency increase, this new ultra-compact packaging technology can suffer of the poor thermal conductivity (about 700 times smaller than silicon one) of the benzocyclobutene (BCB) used as both adhesive and planarization layers in each level of the stack. Thermal simulation was conducted using three-dimensional (3-D) FEM tool to analyze the specific behaviors in such stacked structure and to optimize the design rules. This study first describes the heat transfer limitation through the vertical path by examining particularly the case of the high dissipating sources under small area. First results of characterization in transient regime by means of dedicated test device mounted in single level structure are presented. For the design optimization, the thermal draining capabilities of a copper grid or full copper plate embedded in the intermediate layer of stacked structure are evaluated as a function of the technological parameters and the physical properties. It is shown an interest for the transverse heat extraction under the buffer devices dissipating most the power and generally localized in the peripheral zone, and for the temperature uniformization, by heat spreading mechanism, in the localized regions where the attachment of the thin die is altered. Finally, all conclusions of this analysis are used for the quantitative projections of the thermal performance of a first demonstrator based on a three-levels stacking structure for space application.

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This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

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The material presented in the these notes covers the sessions Modelling of electromechanical systems, Passive control theory I and Passive control theory II of the II EURON/GEOPLEX Summer School on Modelling and Control of Complex Dynamical Systems.We start with a general description of what an electromechanical system is from a network modelling point of view. Next, a general formulation in terms of PHDS is introduced, and some of the previous electromechanical systems are rewritten in this formalism. Power converters, which are variable structure systems (VSS), can also be given a PHDS form.We conclude the modelling part of these lectures with a rather complex example, showing the interconnection of subsystems from several domains, namely an arrangement to temporally store the surplus energy in a section of a metropolitan transportation system based on dc motor vehicles, using either arrays of supercapacitors or an electric poweredflywheel. The second part of the lectures addresses control of PHD systems. We first present the idea of control as power connection of a plant and a controller. Next we discuss how to circumvent this obstacle and present the basic ideas of Interconnection and Damping Assignment (IDA) passivity-based control of PHD systems.

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We have investigated the behavior of bistable cells made up of four quantum dots and occupied by two electrons, in the presence of realistic confinement potentials produced by depletion gates on top of a GaAs/AlGaAs heterostructure. Such a cell represents the basic building block for logic architectures based on the concept of quantum cellular automata (QCA) and of ground state computation, which have been proposed as an alternative to traditional transistor-based logic circuits. We have focused on the robustness of the operation of such cells with respect to asymmetries derived from fabrication tolerances. We have developed a two-dimensional model for the calculation of the electron density in a driven cell in response to the polarization state of a driver cell. Our method is based on the one-shot configuration-interaction technique, adapted from molecular chemistry. From the results of our simulations, we conclude that an implementation of QCA logic based on simple ¿hole arrays¿ is not feasible, because of the extreme sensitivity to fabrication tolerances. As an alternative, we propose cells defined by multiple gates, where geometrical asymmetries can be compensated for by adjusting the bias voltages. Even though not immediately applicable to the implementation of logic gates and not suitable for large scale integration, the proposed cell layout should allow an experimental demonstration of a chain of QCA cells.

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We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

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Using a Ginzburg-Landau model for the magnetic degrees of freedom with coupling to disorder, we demonstrate through simulations the existence of stripelike magnetic precursors recently observed in Co-Ni-Al alloys above the Curie temperature. We characterize these magnetic modulations by means of the temperature dependence of local magnetization distribution, magnetized volume fraction, and magnetic susceptibility. We also obtain a temperature-disorder strength phase diagram in which a magnetic tweed phase exists in a small region between the paramagnetic and dipolar phases.

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This paper is concerned with the modeling and analysis of quantum dissipation phenomena in the Schrödinger picture. More precisely, we do investigate in detail a dissipative, nonlinear Schrödinger equation somehow accounting for quantum Fokker–Planck effects, and how it is drastically reduced to a simpler logarithmic equation via a nonlinear gauge transformation in such a way that the physics underlying both problems keeps unaltered. From a mathematical viewpoint, this allows for a more achievable analysis regarding the local wellposedness of the initial–boundary value problem. This simplification requires the performance of the polar (modulus–argument) decomposition of the wavefunction, which is rigorously attained (for the first time to the best of our knowledge) under quite reasonable assumptions.

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The generation of patient-specific induced pluripotent stem cells (iPSCPSCPSCs) offers unprecedented opportunities for modeling and treating human disease. In combination with gene therapy, the iPSCPSCPSC technology can be used to generate disease-free progenitor cells of potential interest for autologous cell therapy. We explain a protocol for the reproducible generation of genetically corrected iPSCPSCPSCs starting from the skin biopsies of Fanconi anemia patients using retroviral transduction with OCT4, SOX2 and KLF4. Before reprogramming, the fibroblasts and/or keratinocytes of the patients are genetically corrected with lentiviruses expressing FANCA. The same approach may be used for other diseases susceptible to gene therapy correction. Genetically corrected, characterized lines of patient-specific iPSCPSCPSCs can be obtained in 4–5 months.

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The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelationbetween variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

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Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

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Rationale Mephedrone (4-methylmethcathinone) is a still poorly known drug of abuse, alternative to ecstasy or cocaine. Objective The major aims were to investigate the pharmacokineticsa and locomotor activity of mephedrone in rats and provide a pharmacokinetic/pharmacodynamic model. Methods Mephedrone was administered to male SpragueDawley rats intravenously (10 mg/kg) and orally (30 and 60 mg/kg). Plasma concentrations and metabolites were characterized using LC/MS and LC-MS/MS fragmentation patterns. Locomotor activity was monitored for 180240 min. Results Mephedrone plasma concentrations after i.v. administration fit a two-compartment model (α=10.23 h−1, β=1.86 h−1). After oral administration, peak mephedrone concentrations were achieved between 0.5 and 1 h and declined to undetectable levels at 9 h. The absolute bioavailability of mephedrone was about 10 % and the percentage of mephedrone protein binding was 21.59±3.67%. We have identified five phase I metabolites in rat blood after oral administration. The relationship between brain levels and free plasma concentration was 1.85±0.08. Mephedrone induced a dose-dependent increase in locomotor activity, which lasted up to 2 h. The pharmacokineticpharmacodynamic model successfully describes the relationship between mephedrone plasma concentrations and its psychostimulant effect. Conclusions We suggest a very important first-pass effect for mephedrone after oral administration and an easy access to the central nervous system. The model described might be useful in the estimation and prediction of the onset, magnitude,and time course of mephedrone pharmacodynamics as well as to design new animal models of mephedrone addiction and toxicity.

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Rationale Mephedrone (4-methylmethcathinone) is a still poorly known drug of abuse, alternative to ecstasy or cocaine. Objective The major aims were to investigate the pharmacokineticsa and locomotor activity of mephedrone in rats and provide a pharmacokinetic/pharmacodynamic model. Methods Mephedrone was administered to male Sprague-Dawley rats intravenously (10 mg/kg) and orally (30 and 60 mg/kg). Plasma concentrations and metabolites were characterized using LC/MS and LC-MS/MS fragmentation patterns. Locomotor activity was monitored for 180-240 min. Results Mephedrone plasma concentrations after i.v. administration fit a two-compartment model (α=10.23 h−1, β=1.86 h−1). After oral administration, peak mephedrone concentrations were achieved between 0.5 and 1 h and declined to undetectable levels at 9 h. The absolute bioavailability of mephedrone was about 10 % and the percentage of mephedrone protein binding was 21.59±3.67%. We have identified five phase I metabolites in rat blood after oral administration. The relationship between brain levels and free plasma concentration was 1.85±0.08. Mephedrone induced a dose-dependent increase in locomotor activity, which lasted up to 2 h. The pharmacokinetic-pharmacodynamic model successfully describes the relationship between mephedrone plasma concentrations and its psychostimulant effect. Conclusions We suggest a very important first-pass effect for mephedrone after oral administration and an easy access to the central nervous system. The model described might be useful in the estimation and prediction of the onset, magnitude,and time course of mephedrone pharmacodynamics as well as to design new animal models of mephedrone addiction and toxicity.