987 resultados para Robots autònoms -- Sistemes de control


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Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cells finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as ‘ultrasensitivity’ and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating ‘simple’ signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how ‘control-oriented’ models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.

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The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

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An effective control of the ion current distribution over large-area (up to 103 cm2) substrates with the magnetic fields of a complex structure by using two additional magnetic coils installed under the substrate exposed to vacuum arc plasmas is demonstrated. When the magnetic field generated by the additional coils is aligned with the direction of the magnetic field generated by the guiding and focusing coils of the vacuum arc source, a narrow ion density distribution with the maximum current density 117 A m-2 is achieved. When one of the additional coils is set to generate the magnetic field of the opposite direction, an area almost uniform over the substrate of 103 cm2 ion current distribution with the mean value of 45 A m-2 is achieved. Our findings suggest that the system with the vacuum arc source and two additional magnetic coils can be effectively used for the effective, high throughput, and highly controllable plasma processing.

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An innovative and effective approach based on low-pressure, low-frequency, thermally nonequilibrium, high-density inductively coupled plasmas is proposed to synthesize device-quality nanocrystalline silicon (nc-Si) thin films at room temperature and with very competitive growth rates. The crystallinity and microstructure properties (including crystal structure, crystal volume fraction, surface morphology, etc.) of this nanostructured phase of Si can be effectively tailored in broad ranges for different device applications by simply varying the inductive rf power density from 25.0 to 41.7 mW/cm3. In particular, at a moderate rf power density of 41.7 mW/cm3, the nc-Si films feature a very high growth rate of 2.37 nm/s, a high crystalline fraction of 86%, a vertically aligned columnar structure with the preferential (111) growth orientation and embedded Si quantum dots, as well as a clean, smooth and defect-free interface. We also propose the formation mechanism of nc-Si thin films which relates the high electron density and other unique properties of the inductively coupled plasmas and the formation of the nanocrystalline phase on the Si surface.

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This article explores a number of social control strategies on individuals and families actioned by the newly created state-national project during the first decades of Colombian XIX century. With special attention on the discourse of urbanity, also named 'civility or good manners', this paper analyses literary sources produced in the time for molding citizens behaviors in order to incorporate the society into the new paradigm of Modernity.

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Control and diagnostics of low-frequency (∼ 500 kHz) inductively coupled plasmas for chemical vapor deposition (CVD) of nano-composite carbon nitride-based films is reported. Relation between the discharge control parameters, plasma electron energy distribution/probability functions (EEDF/EEPF), and elemental composition in the deposited C-N based thin films is investigated. Langmuir probe technique is employed to monitor the plasma density and potential, effective electron temperature, and EEDFs/EEPFs in Ar + N2 + CH4 discharges. It is revealed that varying RF power and gas composition/pressure one can engineer the EEDFs/EEPFs to enhance the desired plasma-chemical gas-phase reactions thus controlling the film chemical structure. Auxiliary diagnostic tools for study of the RF power deposition, plasma composition, stability, and optical emission are discussed as well.

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This paper presents a modulation and controller design method for paralleled Z-source inverter systems applicable for alternative energy sources like solar cells, fuel cells, or variablespeed wind turbines with front-end diode rectifiers. A modulation scheme is designed based on simple shoot-through principle with interleaved carriers to give enhanced ripple reduction in the system. Subsequently, a control method is proposed to equalize the amount of power injected by the inverters in the grid-connected mode and also to provide reliable supply to sensitive loads onsite in the islanding mode. The modulation and controlling methods are proposed to have modular independence so that redundancy, maintainability, and improved reliability of supply can be achieved. The performance of the proposed paralleled Z-source inverter configuration is validated with simulations carried out using Matlab/Simulink/Powersim. Moreover, a prototype is built in the laboratory to obtain the experimental verifications.

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Capacitors are widely used for power-factor correction (PFC) in power systems. When a PFC capacitor is installed with a certain load in a microgrid, it may be in parallel with the filter capacitor of the inverter interfacing the utility grid and the local distributed-generation unit and, thus, change the effective filter capacitance. Another complication is the possibility of occurrence of resonance in the microgrid. This paper conducts an in-depth investigation of the effective shunt-filter-capacitance variation and resonance phenomena in a microgrid due to a connection of a PFC capacitor. To compensate the capacitance-parameter variation, an Hinfin controller is designed for the voltage-source- inverter voltage control. By properly choosing the weighting functions, the synthesized Hinfin controller would exhibit high gains at the vicinity of the line frequency, similar to traditional high- performance P+ resonant controller and, thus, would possess nearly zero steady-state error. However, with the robust Hinfin controller, it will be possible to explicitly specify the degree of robustness in face of parameter variations. Furthermore, a thorough investigation is carried out to study the performance of inner current-loop feedback variables under resonance conditions. It reveals that filter-inductor current feedback is more effective in damping the resonance. This resonance can be further attenuated by employing the dual-inverter microgrid conditioner and controlling the series inverter as a virtual resistor affecting only harmonic components without interference with the fundamental power flow. And finally, the study in this paper has been tested experimentally using an experimental microgrid prototype.

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In this paper a novel controller for stable and precise operation of multi-rotors with heavy slung loads is introduced. First, simplified equations of motions for the multi-rotor and slung load are derived. The model is then used to design a Nonlinear Model Predictive Controller (NMPC) that can manage the highly nonlinear dynamics whilst accounting for system constraints. The controller is shown to simultaneously track specified waypoints whilst actively damping large slung load oscillations. A Linear-quadratic regulator (LQR) controller is also derived, and control performance is compared in simulation. Results show the improved performance of the Nonlinear Model Predictive Control (NMPC) controller over a larger flight envelope, including aggressive maneuvers and large slung load displacements. Computational cost remains relatively small, amenable to practical implementation. Such systems for small Unmanned Aerial Vehicles (UAVs) may provide significant benefit to several applications in agriculture, law enforcement and construction.

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This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

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Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

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Large arrays and networks of carbon nanotubes, both single- and multi-walled, feature many superior properties which offer excellent opportunities for various modern applications ranging from nanoelectronics, supercapacitors, photovoltaic cells, energy storage and conversation devices, to gas- and biosensors, nanomechanical and biomedical devices etc. At present, arrays and networks of carbon nanotubes are mainly fabricated from the pre-fabricated separated nanotubes by solution-based techniques. However, the intrinsic structure of the nanotubes (mainly, the level of the structural defects) which are required for the best performance in the nanotube-based applications, are often damaged during the array/network fabrication by surfactants, chemicals, and sonication involved in the process. As a result, the performance of the functional devices may be significantly degraded. In contrast, directly synthesized nanotube arrays/networks can preclude the adverse effects of the solution-based process and largely preserve the excellent properties of the pristine nanotubes. Owing to its advantages of scale-up production and precise positioning of the grown nanotubes, catalytic and catalyst-free chemical vapor depositions (CVD), as well as plasma-enhanced chemical vapor deposition (PECVD) are the methods most promising for the direct synthesis of the nanotubes.

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Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

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An advanced inductively coupled plasma (ICP)-assisted rf magnetron sputtering deposition method is developed to synthesize regular arrays of pear-shaped ZnO nanodots on a thin SiNx buffer layer pre-deposited onto a silicon substrate. It is shown that the growth of ZnO nanodots obey the cubic root-law behavior. It is also shown that the synthesized ZnO nanodots are highly-uniform, controllable by the experimental parameters, and also feature good structural and photoluminescent properties. These results suggest that this custom-designed ICP-based technique is very effective and highly-promising for the synthesis of property- and size-controllable highly-uniform ZnO nanodots suitable for next-generation light emitting diodes, energy storage, UV nanolasers, and other applications.

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A combination of laser plasma ablation and strain control in CdO/ZnO heterostructures is used to produce and stabilize a metastable wurtzite CdO nanophase. According to the Raman selection rules, this nanophase is Raman-active whereas the thermodynamically preferred rocksalt phase is inactive. The wurtzite-specific and thickness/strain-dependent Raman fingerprints and phonon modes are identified and can be used for reliable and inexpensive nanophase detection. The wurtzite nanophase formation is also confirmed by x-ray diffractometry. The demonstrated ability of the metastable phase and phonon mode control in CdO/ZnO heterostructures is promising for the development of next-generation light emitting sources and exciton-based laser diodes.