Optimal Predictive Control of Three-Phase NPC Multilevel Converter for Power Quality Applications

This paper presents the optimal control of the ac currents, the dc voltage regulation, and the dc capacitor voltage balancing in a three-level three-phase neutral point clamped multilevel converter for use in power quality applications as an active power filter. The ac output currents and the dc capacitor voltages are sampled and predicted for the next sampling time using linearized models and considering all the 27 output voltage vectors. A suitable quadratic weighed cost function is used to choose the voltage vector that minimizes the ac current tracking errors, the dc voltage steady-state error, and the input dc capacitor voltage unbalancing. The obtained experimental results show that the output ac currents track their references showing small ripple, a total harmonic distortion (THD) of less than 1%, harmonic contents that are 46 dB below the fundamental, and almost no steady-state error (0.3%). The capacitor voltages are balanced within 0.05%, and the balancing is assured even when redundant vectors are not chosen. Near-perfect capacitor dc voltage balancing is obtained while reducing current harmonic distortion. Some experimental evidence of robustness concerning a parameter variation was also found, with the optimum controller withstanding parameter deviations from $+$100% to $-$50%. Compared to a robust sliding mode controller, the optimal controller can reduce the THD of the ac currents or reduce the switching frequency at the same THD, being a suitable controller for power quality in medium-voltage applications.      

A fast and efficient hybrid fractal-wavelet image coder.

The excellent visual quality and compression rate of fractal image coding have limited applications due to exhaustive inherent encoding time. This paper presents a new fast and efficient image coder that applies the speed of the wavelet transform to the image quality of the fractal compression. Fast fractal encoding using Fisher's domain classification is applied to the lowpass subband of wavelet transformed image and a modified set partitioning in hierarchical trees (SPIHT) coding, on the remaining coefficients. Furthermore, image details and wavelet progressive transmission characteristics are maintained, no blocking effects from fractal techniques are introduced, and the encoding fidelity problem common in fractal-wavelet hybrid coders is solved. The proposed scheme promotes an average of 94% reduction in encoding-decoding time comparing to the pure accelerated Fractal coding results. The simulations also compare the results to the SPIHT wavelet coding. In both cases, the new scheme improves the subjective quality of pictures for high-medium-low bitrates.     

3D Printing and Nanotechnology: A Multiscale Alliance in Personalized Medicine

3D printing and nanotechnology have been two important tools in the development of therapeutic approaches for personalized medicine. More recently, their alliance has been improved in an effort to build innovative, versatile, multifunctional, and/or smart medical and pharmaceutical products. Therefore, an extensive review about scientific studies that ally 3D printing and nanomaterials in the development of new approaches for pharmaceutical and medical applications for the treatment and prevention of diseases is presented here. The articles are classified into five categories according to their main application: Cell growth and tissue engineering, antimicrobial, drug delivery, stimulus-response, and theranostics. Semisolid extrusion, inorganic nanoparticles, and cell growth and tissue engineering are the most reported 3D printing technique, type of nanomaterial, and application, respectively. The increase in papers dedicated to these areas is also notable, especially in the 2019 and 2020, when semisolid extrusion became the most used technique, overcoming fused deposition modelling. In fact, this review highlights that the possibility of an alliance between 3D printing and nanotechnology for the production of multiscale materials is undoubtedly a great opportunity for knowledge and innovation in the pharmaceutical and medical area.     

Deriving Efficient Porous Heteroatom‐Doped Carbon Electrocatalysts for Hydrazine Oxidation from Transition Metal Ions‐Coordinated Casein

In this work, the synthesis of high‐performance, metal ion‐imprinted, mesoporous carbon electrocatalysts for hydrazine oxidation reaction (HzOR) using casein or a family of phosphoproteins derived from cow's milk as a precursor is shown. The synthesis is made possible by mixing trace amounts of non‐noble metal ions (Fe³⁺ or Co²⁺) with casein and then producing different metal ions‐functionalized casein intermediates, which upon carbonization, followed by acid treatment, lead to metal ion‐imprinted catalytically active sites on the materials. The materials effectively electrocatalyze HzOR with low overpotentials at neutral pH and exhibit among the highest electrocatalytic performances ever reported for carbon catalysts. Their catalytic activities are also better than the corresponding control material, synthesized by carbonization of pure casein and other materials previously reported for HzOR. This work demonstrates a novel synthetic route that transforms an inexpensive protein to highly active carbon‐based electrocatalysts by modifying its surfaces with trace amounts of non‐noble metals. The types of metal ions employed in the synthesis are found to dictate the electrocatalytic activities of the materials. Notably, Fe³⁺ is found to be more effective than Co²⁺ in helping the conversion of casein into more electrocatalytically active carbon materials for HzOR.     

Design and development of two-dimensional position sensitive photo-detector

Position sensitive photo-detectors (PSDs) utilize the lateral photovoltaic effect to produce an electrical output that varies linearly with the position of a light spot incident on a semiconductor junction. Design, fabrication and characterization of newly developed silicon PSD, which employ the planar technology and double ion implantation with different doses, are described. Shallow and low-doped p-n junction is formed by boron implantation in n-type silicon substrate. The position characteristics of PSD are symmetric to the zero and linear in the 80% of the active area. For a higher resistivity top layer (lower implanted dose), the sensitivity grows up and the linearity gets improved. The influence of the substrate is not substantial for the position characteristics. The response of the sensor, measured by pulsed 15 ns laser, was determined to be about 100 ns. Described PSD has been used in the construction of simple light spot rotational follower.     

Video coding using greedy decompositions on generalised bit-planes

A novel method for performing greedy decompositions using generalised bit-planes is proposed. It provides an elegant solution to the tradeoff between quantisation of coefficients and number of passes in the matching pursuits algorithm. In addition, when replacing the matching pursuits algorithm in video coding, it provides a significant performance improvement     

Integrated structure and control design for mechatronic systems with configuration-dependent dynamics

This paper considers the optimal design of mechatronic systems with configuration-dependent dynamics. An optimal mechatronic design requires that, among the structural and control parameters, an optimal choice has to be made with respect to design specifications in the different domains. Two main challenges are treated in this paper: the non-convex nature of the optimization problem and the difficulty in modeling serial machines with flexible components and their embedded controllers. The optimization problem is treated using the direct design strategy which considers simultaneously structural and control parameters as variables and adopts non-convex optimization algorithms. Linear time-invariant and gain-scheduling PID controllers are addressed. This methodology is exploited for the multi-objective optimization of a pick-and-place assembly robot with a gripper carried by a variable-length flexible beam. The resulting design tradeoffs between system accuracy and control efforts demonstrate the advantage of an integrated design approach for mechatronic systems with configuration-dependent dynamics.     

High-Performance ITO-Free Perovskite Solar Cells Enabled by Single-Walled Carbon Nanotube Films

The unprecedented advancement in power conversion efficiencies (PCEs) of perovskite solar cells (PSCs) has rendered them a promising game-changer in photovoltaics. However, unsatisfactory environmental stability and high manufacturing cost of window electrodes are bottlenecks impeding their commercialization. Here, a strategy is introduced to address these bottlenecks by replacing the costly indium tin oxide (ITO) window electrodes via a simple transfer technique with single-walled carbon nanotubes (SWCNTs) films, which are made of earth-abundant elements with superior chemical and environmental stability. The resultant devices exhibit PCEs of ≈19% on rigid substrates, which is the highest value reported to date for ITO-free PSCs. The facile approach for SWCNTs also enables application in flexible PSCs (f-PSCs), delivering a PCE of ≈18% with superior mechanical robustness over their ITO-based counterparts due to the excellent mechanical properties of SWCNTs. The SWCNT-based PSCs also deliver satisfactory performances on large-area (1 cm² active area in this work). Furthermore, these SWCNT-based PSCs can retain over 80% of original PCEs after exposure to air over 700 h while ITO-based devices only sustain ≈60% of initial PCEs. This work paves a promising way to accelerate the commercialization of ITO-free PSCs with reduced material cost and prolonged lifetimes.     

Use of support vector regression and numerically predicted cloudiness to forecast power output of a photovoltaic power plant in Kitakyushu,Japan

The development of a methodology to forecast accurately the power produced by photovoltaic systems can be an important tool for the dissemination and integration of such systems on the public electricity grids. Thus, the objective of this study was to forecast the power production of a 1‐MW photovoltaic power plant in Kitakyushu, Japan, using a new methodology based on support vector machines and on the use of several numerically predicted weather variables, including cloudiness. Hourly forecasts of the power produced for 1 year were carried out. Moreover, the effect of the use of numerically predicted cloudiness on the quality of the forecasts was also investigated. The forecasts of power production obtained with the proposed methodology had a root mean square error of 0.0948 MW h and a mean absolute error of 0.058 MW h. It was also found that the forecast and measured values of power production had a good level of correlation varying from 0.8 to 0.88 according to the season of the year. Finally, the use of numerically predicted cloudiness had an important role in the accuracy of the forecasts, and when cloudiness was not used, the root mean square error of the forecasts increased more than 32%, and the mean absolute error increased more than 42%. Copyright © 2011 John Wiley & Sons, Ltd.