A robust model-free controller for a three-phase grid-connected photovoltaic system based on ultra-local model

In this paper, a robust model-free controller for a grid-connected photovoltaic (PV) system is designed. The system consists of a PV generator connected to a three-phase grid by a DC/AC converter. The control objectives of the overall system are to extract maximum power from the PV source, to control reactive power exchange and to improve the quality of the current injected into the grid. The model-free control technique is based on the use of an ultra-local model instead of the dynamic model of the overall system. The local model is continuously updated based on a numerical differentiator using only the input–output behavior of the controlled system. The model-free controller consists of a classical feedback controller and a compensator for the effects of internal parameter changes and external disturbances. Simulation results illustrate the efficiency of the controller for grid-connected PV systems.     

Comparison of Thin Films of Titanium Dioxide Deposited by Sputtering and Sol–Gel Methods for Waveguiding Applications

Semiconductors - In this work, TiO2 thin films were deposited onto glass substrate by two different techniques: sol–gel dip-coating (SG) and reactive DC magnetron sputtering (Sput). The...     

A sliding mode control and artificial neural network based MPPT for a direct grid‐connected photovoltaic source

A robust sliding mode controller for a grid‐connected photovoltaic source is proposed in this paper. The objective of the presented control scheme is to force both the output voltage of the photovoltaic PV source and the power factor at the inverter output to follow a certain trajectory reference. The main idea is to apply the robust sliding mode controller directly to the nonlinear state model of the system composed of the PV source and the inverter with its input and output filters. In order to operate the PV system at the maximum power point and to satisfy the environmental factors, such as solar irradiance and temperature, we included a rigorous maximum power point tracker based on an artificial neural network. Simulation results are presented to illustrate the performance of the proposed control scheme. In addition, we show that the grid current satisfies the harmonic limits of the IEEE standard for interconnecting distributed energy sources with electric power systems.     

Energy efficiency of cement finish grinding in a dry batch ball mill

Dry grinding experiments on cement clinker were carried out using a laboratory batch ball mill equipped with torque measurement. The specific energy was found to be dependent on operating parameters and clinker environment. Additional compounds such as gypsum and pozzolanic tuff improve energy efficiency. The optimal parameters allowing maximising the energy efficiency factor were determined. Energy efficiency factors were obtained both on the crude material (size minus 2.8 mm) and on a sieved fraction (1-0.71 mm). They demonstrate that a low initial rate of breakage implies higher energy efficiency. On the contrary, conditions ensuring an initial maximal rate of breakage lead to an increase of the energy consumption.     

Pertraction of xylene isomers using cyclodextrin-containing membranes: mass transport mechanism and modelling

The use of water across Europe varies on a country and regional level due to different climates, cultures, economies, and natural as well as political circumstances. All European countries have the following concerns in common: how to deal with water, how to satisfy the water demand for households, industry and agriculture, and how to protect the aquatic environment and ecosystems. Nowadays, wastewater reuse is becoming an economically and environmentally sound method for integrated water management. The implementation of wastewater reclamation, recycling and reuse promotes the preservation of limited water resources and becomes an attractive option for conserving and extending available water supplies. On the basis of wastewater availability for supplemental applications prior to discharge or disposal, water reuse appears to be a suitable practice with potentially beneficial use. This paper describes the potential for greater wastewater reuse in the Czech Republic. On the basis of a country-wide analysis of the water management situation, different regions were identified with particular water stress problems. The first water stressed region was identified on the basis of insufficient surface water quality where most of the rivers were ranked into the water quality category V. This region is known as an industrial area, and hence there is a possibility to reuse wastewater for industrial purposes. The second investigated region is in a rain shadow area and can be characterised as water stressed in terms of climatic conditions. This area is in the south of Moravia, which is famous for agricultural production, and there is a potential to reuse wastewater for agricultural purposes.     

Preparation and characterization of α-cyclodextrin-containing membranes—application to the selective extraction of xylene isomers

Polymer membranes containing α-cyclodextrin (α-CD) were prepared by the casting method using cross-linking reaction with hexamethylenediisocyanate. The film synthesis conducted with and without dibutyltin dilaurate as catalyst, resulted in two series of materials in which α-CD host entities were chemically linked to polyvinyl alcohol and physically entrapped, respectively. The obtained membranes were successfully applied to the separation of o-/p- and o-/m-xylene isomer mixtures by pertraction from water. p- and m-xylenes were found to be the faster permeants compared to the o-isomer. The separation factor of p-xylene over o-xylene varied from 7.75 to 0.35 depending on the membrane α-CD content and the feed concentration ratio. Permeation rate and separation selectivity data were discussed in terms of molecular recognition by α-CD and of coupling transport effect. Both kinds of materials showed similar behaviour in their permeation performances indicating that inclusion interaction was not changed by the chemical grafting on PVA chains.     

On-line monitoring of vacuum drying of theophylline using NIR spectroscopy: solid-state transitions,water content and semi-empirical modeling

The aim of this work was to monitor in-line and at a real time, the solid-state forms during pharmaceuticals manufacturing. It concerns the dehydration behavior and the solid-state transitions of theophylline in an agitated vacuum contact dryer. First, a near infrared spectroscopy (NIRS) method was performed using a reflectance diffuse probe to measure the in-line and in-situ exact composition of the mixture of different forms of theophylline and water content during drying. A multivariate modeling has been investigated to build a robust model which can predict four components at the same time during drying process. The XRPD analysis was used as a reference method in the process of calibration of NIRS. The indicators of the accuracy in quantitative spectral analysis confirm the robustness of the model and the efficiency of the method of calibration. Second, the kinetics of solid state transformations were investigated. It was shown that the dehydration advanced first by the formation of the metastable anhydrate and after a lag time of the stable one. Once the stable form appeared, formation of the metastable form came to an end. The temperature was found out to be the main factor controlling the overall process rate but also the final contents of the stable and metastable anhydrates for the considered dryer and operating conditions range. Finally, a semi-empirical drying model was proposed and significant quantitative differences were found, particularly at the product temperature which was probably caused by the excessive simplicity of the model.     

Learning spatially correlation filters based on convolutional features via PSO algorithm and two combined color spaces for visual tracking

Last years, we have seen an emergence of wide methods in visual object tracking topic as convolutional neural network combined with correlation filter such as hierarchical features (HCF) (Ma et al. 20). However, upon the fact that some features may cause the tracking failures, the existing methods are still suffering of handling complex object appearance changes such as fast motion, significant deformation and occlusions. Further, they learn the correlation filter in frequency domain using Fourier transform, which cause unwanted boundary effects, which severely degrade the quality of the tracking model. Moreover, these methods are incapable of dealing with the illumination variation because they rely only on RGB base for color sequences. In this paper, we propose a novel method, which addresses the pre-cited problems. As first contribution, we learn adaptively three correlation filters in the spatial domain, with hierarchical convolutional features extracted from specific layers. Indeed, we apply the Particle Swarm Optimization algorithm to solve the update model equation of the correlation filters. Second, we propose that the switching between RGB and HSV color bases, give a soft manner to handle the illumination variation. For this aim, an HSV-energy condition is presented to choose the appropriate color base resorting to the energy of the second HSV component. Extensive experiments on a common benchmark dataset, justify that the proposed method outperforms the state-of-art methods.