975 resultados para varactor tuning


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Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

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This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

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The common goal of tissue engineering is to develop substitutes that can closely mimic the structure of extracellular matrix (ECM). However, similarly important is the intensive material properties which have often been overlooked, in particular, for soft tissues that are not to bear load assumingly. The mechanostructural properties determine not only the structural stability of biomaterials but also their physiological functionality by directing cellular activity and regulating cell fate decision. The aim here is to emphasize that cells could sense intensive material properties like elasticity and reside, proliferate, migrate and differentiate accordinglyno matter if the construct is from a natural source like cartilage, skin etc. or of synthetic one. Meanwhile, the very objective of this work is to provide a tunable scheme for manipulating the elasticity of collagen-based constructs to be used to demonstrate how to engineer cell behavior and regulate mechanotransduction. Articular cartilage was chosen as it represents one of the most complex hierarchical arrangements of collagen meshwork in both connective tissues and ECM-like biomaterials. Corona discharge treatment was used to produce constructs with varying density of crosslinked collagen and stiffness accordingly. The results demonstrated that elastic modulus increased up to 33% for samples treated up to one minute as crosslink density was found to increase with exposure time. According to the thermal analysis, longer exposure to corona increased crosslink density as the denaturation enthalpy increased. However the spectroscopy results suggested that despite the stabilization of the collagen structure the integrity of the triple helical structure remained intact. The in vitro superficial culture of heterologous chondrocytes also determined that the corona treatment can modulate migration with increased focal adhesion of cells due to enhanced stiffness, without cytotoxicity effects, and providing the basis for reinforcing three-dimensional collagen-based biomaterials in order to direct cell function and mediate mechanotransduction.

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Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.

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Different magnetization in vertical graphenes fabricated by plasma-enabled chemical conversion of organic precursors with various oxygen atom contents and bonding energies was achieved. The graphenes grown from fat-like precursors exhibit magnetization up to 8 emu g−1, whereas the use of sugar-containing precursors results in much lower numbers. A relatively high Curie temperature exceeding 600 K was also demonstrated.

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A simple, uniquely plasma-enabled and environment-friendly process to reduce the thickness of vertically standing graphenes to only 4–5 graphene layers and arranging them in dense, ultra-large surface area, ultra-open-edge-length, self-organized and interconnected networks is demonstrated. The approach for the ultimate thickness reduction to 1–2 graphene layers is also proposed. The vertical graphene networks are optically transparent and show tunable electric properties from semiconducting to semi-metallic and metallic at room and near-room temperature, thus recovering semi-metallic properties of a single-layer graphene.

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Failures on rolling element bearings usually originate from cracks that are detectable even in their early stage of propogation by properly analyzing vibration signals measured in the proximity of the bearing. Due to micro-slipping in the roller-races contact, damage-induced vibration signals belong to the family of quasi-periodic signals with a strong second order cyclostationary component. Cyclic coherence and its integrated form are widely considered as the most suitable tools for bearing fault diagnostics and their theoretical bases have been already consolidated. This paper presents how to correctly set the parameters of the cyclostationary analysis tool to be implemented in an automatable algorithm. In the first part of the paper some general guidelines are provided for the specific application. These considerations are further verified, applying cyclostationary tools to data collected in an experimental campaign on a specific test-rig.

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Nowadays, integration of small-scale electricity generators, known as Distributed Generation (DG), into distribution networks has become increasingly popular. This tendency together with the falling price of DG units has a great potential in giving the DG a better chance to participate in voltage regulation process, in parallel with other regulating devices already available in the distribution systems. The voltage control issue turns out to be a very challenging problem for distribution engineers, since existing control coordination schemes need to be reconsidered to take into account the DG operation. In this paper, a control coordination approach is proposed, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimize the interaction of DG with another DG or other active devices, such as On-load Tap Changing Transformer (OLTC). The proposed technique has been developed based on the concepts of protection principles (magnitude grading and time grading) for response coordination of DG and other regulating devices and uses Advanced Line Drop Compensators (ALDCs) for implementation. A distribution feeder with tap changing transformer and DG units has been extracted from a practical system to test the proposed control technique. The results show that the proposed method provides an effective solution for coordination of DG with another DG or voltage regulating devices and the integration of protection principles has considerably reduced the control interaction to achieve the desired voltage correction.

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In 2005, natural sequence farming founder Peter Andrews was featured on ABC TV’s Australian Story, since voted one of the top five episodes of the last 10 years. His book Back from the Brink is a national bestseller. Why are Andrews’ ideas attracting so much attention?

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The capabilities of the mechanical resonator-based nanosensors in detecting ultra-small mass or force shifts have driven a continuing exploration of the palette of nanomaterials for such application purposes. Based on large-scale molecular dynamics simulations, we have assessed the applicability of a new class of carbon nanomaterials for nanoresonator usage, i.e. the single-wall carbon nanotube (SWNT) network. It is found that SWNT networks inherit excellent mechanical properties from the constituent SWNTs, possessing a high natural frequency. However, although a high quality factor is suggested from the simulation results, it is hard to obtain an unambiguous Q-factor due to the existence of vibration modes in addition to the dominant mode. The nonlinearities resulting from these extra vibration modes are found to exist uniformly under various testing conditions including different initial actuations and temperatures. Further testing shows that these modes can be effectively suppressed through the introduction of axial strain, leading to an extremely high quality factor in the order of 109 estimated from the SWNT network with 2% tensile strain. Additional studies indicate that the carbon rings connecting the SWNTs can also be used to alter the vibrational properties of the resulting network. This study suggests that the SWNT network can be a good candidate for applications as nanoresonators.

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Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

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Better operational control of water networks can help reduce leakage, maintain pressure, and control flow. Proportional integral derivative (PID) controllers, with proper fine-tuning, can help water utility operators achieve targets faster without creating undue transients. The authors compared three tuning methods, in different test situations, involving flow and level control to different reservoirs. Although target values were reached with all three tuning methods, the methods’ performances varied significantly. The lowest performer among the three was the method most widely used in the industry—standard tuning by the Ziegler-Nichols method. Achieving better results was offline tuning by genetic algorithms. Achieving the best control, though, was a fuzzy logic–based online tuning approach—the FZPID controller. The FZPID controller had fewer overshoots and took significantly less time to tune the gains for each problem. This new tuning approach for PID controllers can be applied to a variety of problems and can increase the performance of water networks of any size and structure