Skysčio lygio valdymas taikant fuzzy logiką

Nagrinėjamas skysčio lygio valdymas nevienalytės formos talpykloje, taikant fuzzy ir proporcingąjį integralinį (PI) reguliatorius. Trumpai supažindinama su fuzzy logika, priklausomybės funkcijos, fuzzy aibės sąvokomis. Pateikiamas fuzzy reguliatoriaus architektūros modelis. Sudaryti skysčio talpyklos, lygio fuzzy ir PI reguliatorių matematinis ir imitacinis modeliai. Pateikiami imitacijos rezultatai, gauti taikant paketo MATLAB priedą Simulink. Imitacijos rezultatai, skysčio lygį valdant „žemyn“, įrodo, kad, naudojant tradicinį PI reguliatorių, gaunamas didelis dinaminis nuokrypis ir ilga pereinamojo proceso trukmė. Pereinamojo proceso kokybę galima pagerinti pritaikius fuzzy reguliatorių. Tai padarius labai sumažėjo dinaminis nuokrypis ir pereinamojo proceso trukmė

Controller for the Grid-Connected Microinverter Output Current Tracking

The modification of the proportional–integral (PI) controller with the variable proportional constant for tracking of the grid-connected photovoltaic microinverter output current has been proposed. The obtained results show that in the case when the proportional constant of the PI controller varies in time according to the appropriate law, the microinverter output current sinus shape distortions decrease as compared to the case when the ordinary PI controller is used. The operation of the microinverter with the proposed controller was investigated for the cases when the electrical grid voltage sinus shape is not distorted and when it is distorted by the higher harmonics

Flyback mikroinverterio, sudaryto iš dviejų raktų, modelio Matlab Simulink aplinkoje sudarymas ir tyrimas / Development and research of two switch based Flyback microconverter’s Matlab Simulink model

Paper describes simulation results of proposed micro inverter model based on flyback converter with two transistor switches using Matlab Simulink. The aim of this research to investigate behavior of proposed model of the micro inverter based on flyback converter, when micro inverter operates autonomously (islanding) and running parallel in the local electricity network. The simulation of micro inverter’s operation on autonomous mode using nonlinear load was performed, as well as it runs in parallel with the local power network polluted with harmonics. The main goal of these simulations is to observe the response of output current of micro inverter to the harmonical distortions of local grid. Examination of the proposed micro inverter model based on flyback converter in Matlab Simulink environment helps to determinate the resistance of micro inverter output signal to distortion in local electrical grid using two working modes: 1. the autonomous mode using nonlinear load, 2. the parallel mode with local electric grid polluted by higher order harmonics. Santrauka Darbe pateikti siūlomo flyback tipo mikroinverterio, sudaryto iš dviejų raktų, modeliavimo rezultatai Matlab Simulink aplinkoje. Tyrimo tikslas – įvertinti siūlomo flyback mikroinverterio modelio veikimą virtualioje Matlab Simulink aplinkoje, kai mikroinverteris veikia autonomiškai (energetinėje saloje) ir lygiagrečiai su vietiniu elektros tinklu. Darbe imituojamas autonomiškas mikroinverterio darbas su netiesiniais elektros tinklo apkrovos elementais ir harmonikomis užterštame elektros tinkle. Taip siekiama įvertinti mikroinverterio tiekiamos į tinklą sinusinės formos srovės reakciją į tinklo įtampos harmoninius iškraipymus. Ištyrus pasiūlyto flyback mikroinverterio eksperimentinį modelį Matlab Simulink aplinkoje, nustatytas mikroinverterio išėjimo signalo atsparumas iškraipymams jam veikiant autonomiškai ir imituojant elektros tinklą, paveiktą aukštesniosiomis eilės harmonikomis. Reikšminiai žodžiai: flyback keitiklis, mikroinverteris, viršįtampiai, elektros tinklas, PID reguliatorius, harmonikos

Automatic particle detectors lead to a new generation in plant diversity investigation

Technological progress in modern scientific development generates opportunities that create new ways to learn more about objects and systems of nature. An important indicator in choosing research methods is not only accuracy but also the time and human resources required to achieve results. This research demonstrates the possibilities of using an automatic particle detector that works based on scattered light pattern and laser-induced fluorescence for plant biodiversity investigation. Airborne pollen data were collected by two different devices, and results were analysed in light of the application for plant biodiversity observation. This paper explained the possibility to gain knowledge with a new type of method that would enable biodiversity monitoring programs to be extended to include information on the diversity of airborne particles of biological origin. It was revealed that plant conservation could be complemented by new tools to test the effectiveness of management plans and optimise mitigation measures to reduce impacts on biodiversity

Clustering approach for the analysis of the fluorescent bioaerosol collected by an automatic detector

Automatically operating particle detection devices generate valuable data, but their use in routine aerobiology needs to be harmonized. The growing network of researchers using automatic pollen detectors has the challenge to develop new data processing systems, best suited for identification of pollen or spore from bioaerosol data obtained near-real-time. It is challenging to recognise all the particles in the atmospheric bioaerosol due to their diversity. In this study, we aimed to find the natural groupings of pollen data by using cluster analysis, with the intent to use these groupings for further interpretation of real-time bioaerosol measurements. The scattering and fluorescence data belonging to 29 types of pollen and spores were first acquired in the laboratory using Rapid-E automatic particle detector. Neural networks were used for primary data processing, and the resulting feature vectors were clustered for scattering and fluorescence modality. Scattering clusters results showed that pollen of the same plant taxa associates with the different clusters corresponding to particle shape and size properties. According to fluorescence clusters, pollen grouping highlighted the possibility to differentiate Dactylis and Secale genera in the Poaceae family. Fluorescent clusters played a more important role than scattering for separating unidentified fluorescent particles from tested pollen. The proposed clustering method aids in reducing the number of false-positive errors

Comparison of computer vision models in application to pollen classification using light scattering

This study investigates the use of pollen elastically scattered light images for species identification. The aim was to identify the best recognition algorithms for pollen classification based on the scattering images. A series of laboratory experiments with a Rapid-E device of Plair S.A. was conducted collecting scattering images and fluorescence spectra from pollen of 15 plant genera. The collected scattering data were supplied to 32 different setups of 8 computer vision models based on deep neural networks. The models were trained to classify the pollen types, and their performance was compared for the test sub-samples withheld from the training. Evaluation showed that most of the tested computer vision models convincingly outperform the basic convolutional neural network used in our previous studies: the accuracy gain was approaching 10% for best setups. The models of the Weakly Supervised Object Detection approach turned out to be the most accurate, but also slow. However, even the best setups still did not provide sufficient recognition accuracy barely reaching 65%–70% in the repeated tests. They also showed many false positives when applied to real-life time series collected by Rapid-E. Similar to the previous studies, fusion of the new scattering models with the fluorescence-based identification demonstrated almost 15% higher skills than either of the approaches alone reaching 77–83% of the overall classification accuracy

Detection and Microscopy of Alnus glutinosa Pollen Fluorescence Peculiarities

Alnus glutinosa is an important woody plant in Lithuanian forest ecosystems. Knowledge of fluorescence properties of black alder pollen is necessary for scientific and practical purposes. By the results of the study, we aimed to evaluate possibilities of identifying Alnus glutinosa pollen fluorescence properties by modeling ozone effect and applying two different fluorescence-based devices. To implement the experiments, black alder pollen was collected in a typical habitat during the annual flowering period in 2018–2019. There were three groups of experimental variants, which differed in the duration of exposure to ozone, conditions of pollen storage before the start of the experiment, and the exposure time. Data for pollen fluorescence analysis were collected using two methods. The microscopy method was used in order to evaluate the possibility of employing image analysis systems for investigation of pollen fluorescence. The second data collection method is related to an automatic device identifying pollen in real time, which uses the fluorescence method in the pollen recognition process. Data were assessed employing image analysis and principal component analysis (PCA) methods. Digital images of ozone-exposed pollen observed under the fluorescence microscope showed the change of the dominant green colour toward the blue spectrum. Meanwhile, the automatic detector detects more pollen whose fluorescence is at the blue light spectrum. It must be noted that assessing pollen fluorescence several months after exposure to ozone, no effect of ozone on fluorescence remains