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Four-Channel Buck Converter in Asymmetrical Continuous Current Conduction Mode

Canadian Journal of Electrical and Computer Engineering 2020年第4期43卷 251-260页

作者： Litvani, Lilla Hamar, Janos Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

This article is concerned with the asymmetrical control strategies of a four-channel dc/dc buck converter in the continuous current conduction mode (CCM). The converter has two input and four output channels. Energy equations of the converter are studied, and asymmetry of input voltages, output voltages, and loads are examined in the CCM. The proposed control strategy allows us to directly control the power flow in each channel without any unwanted consequences for the rest of the channels among these conditions. The main advantage is the direct control of the total transferred power by the positive sequence of the capacitor voltage, the power exchange among the input channels by the negative sequence of the capacitor voltage, and the power exchange among the output channels by the inductor currents. Calculating these currents also helps to determine whether the converter at a certain point operates in the CCM or in the boundary mode (where zero current switching is possible). Feasibility of zero-voltage switching is simplified by this method. Converter efficiency is showed to be 83% at asymmetrical output voltages in the CCM. Theoretical studies are confirmed by both numerical simulations and laboratory experiments on a 100-W prototype. The studied converter can be applied in supplying multilevel inverters. © 2003-2010 IEEE Canada.

关键词： Zero current switching

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Privacy-Preserving Utilization of Distribution System Flexibility for Enhanced TSO-DSO Interoperability: A Novel Machine Learning-Based Optimal Power Flow Approach

arXiv

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arXiv 2025年

作者： Dindar, Burak Saner, Can Berk Çakmak, Hüseyin K. Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Electrical and Computer Engineering National University of Singapore Singapore117581 Singapore

Due to the transformation of the power system, the effective use of flexibility from the distribution system (DS) is becoming crucial for efficient network management. Leveraging this flexibility requires interoperability among stakeholders, including Transmission System Operators (TSOs) and Distribution System Operators (DSOs). However, data privacy concerns among stakeholders present significant challenges for utilizing this flexibility effectively. To address these challenges, we propose a machine learning (ML)-based method in which the technical constraints of the DSs are represented by ML models trained exclusively on non-sensitive data. Using these models, the TSO can solve the optimal power flow (OPF) problem and directly determine the dispatch of flexibility-providing units (FPUs)—in our case, distributed generators (DGs)-in a single round of communication. To achieve this, we introduce a novel neural network (NN) architecture specifically designed to efficiently represent the feasible region of the DSs, ensuring computational effectiveness. Furthermore, we incorporate various PQ charts rather than idealized ones, demonstrating that the proposed method is adaptable to a wide range of FPU characteristics. To assess the effectiveness of the proposed method, we benchmark it against the standard AC-OPF on multiple DSs with meshed connections and multiple points of common coupling (PCCs) with varying voltage magnitudes. The numerical results indicate that the proposed method achieves performant results while prioritizing data privacy. Additionally, since this method directly determines the dispatch of FPUs, it eliminates the need for an additional disaggregation step. By representing the DSs technical constraints through ML models trained exclusively on nonsensitive data, the transfer of sensitive information between stakeholders is prevented. Consequently, even if reverse engineering is applied to these ML models, no sensitive data can be extracted. This allows

关键词： Reverse engineering

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Prediction of Parkinson’s disease based on artificial neural networks using speech datasets

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13571-13584页

作者： Liu, Wei Liu, Jierong Peng, Tao Wang, Guojun Balas, Valentina Emilia Geman, Oana Chiu, Hung-Wen School of Information and Communication Engineering Hainan University Hainan Haikou570228 China School of Computer Science and Cyber Engineering Guangzhou University Guangdong Guangzhou510006 China College of Biomedical Information and Engineering Hainan Medical University Street Hainan Haikou571199 China Department of Automation and Applied Informatics Aurel Vlaicu University of Arad Arad310130 Romania Department of Health and Human Development Stefan cel Mare University of Suceava Suceava720229 Romania Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan

Parkinson’s disease (PD) is a progressive disorder of the nervous system that affects movement. Early prediction of PD can increase the chances of earlier intervention and delay the onset of the disease. Vocal impairment is one of the most important signs in the early stages of PD. Therefore, PD detection based on speech analysis and vocal patterns has attracted significant attention recently. In this paper, we propose a vowel-based artificial neural network (ANN) model for PD prediction based on single vowel phonation. Firstly, we propose a novel multi-layer neural network based on speech features to predict PD. The speech samples from 48 PD patients and 20 healthy individuals are processed into four types: vowel, number, word, and short sentence. Secondly, we establish ANN models with single-type speech samples versus combinations of multi-type speech samples, respectively. Comparative experiments demonstrate that the single-type vowel model is superior to other single-type models as well as multi-type models. Finally, we build a vowel-based ANN model for PD prediction and evaluate its performance. Extensive experiments demonstrate that the proposed model has a prediction accuracy of 91%, sensitivity of 99%, specificity of 82%, and area under the receiver operating characteristic curve (AUC) of 91%, which is superior to the performance of previous methods. Overall, this study demonstrates that the proposed model can provide good classification accuracy for predicting PD and can improve the rate of early diagnosis. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Network layers

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Dissolved ozone sensing in water and blood based on commercial screen-printed and BDD electrodes

Dissolved ozone sensing in water and blood based on commerci...

引用

IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Lisa Petani Lea Llupa Zhen Peng Genki Ogata Liane Koker Ulrich Gengenbach Yasuaki Einaga Christian Pylatiuk Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Chemistry Keio University Yokohama Japan

Dissolved ozone sensing in water is crucial for a variety of applications, including water treatment, food processing, and medical therapies, as ozone is widely used as an oxidising agent in these processes. Furthermore, dissolved ozone sensing in blood is important for medical therapies. We present a novel dissolved ozone sensor for measurement in water, based on commercially available screen-printed electrodes covered with different porous membranes made of polytetrafluoroethylene (PTFE) and non porous membranes made of polydimethylsiloxane (PDMS). With PTFE, a root mean squared error (RMSE), which is the difference between the novel sensor and the reference spectrometer, of 3.62 mg l −1 can be achieved, while with PDMS a RMSE of 6.34 mg l −1 is obtained. Also, we investigated the measurement of dissolved ozone in blood with membrane-free and electrolyte-free boron-doped diamond (BDD) electrodes. The proposed dissolved ozone sensors offer a promising solution for inexpensive monitoring of dissolved ozone concentrations in water and blood with a compact design.

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Input and state constrained inverse optimal control with application to power networks

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IFAC-PapersOnLine 2023年第2期56卷 5451-5456页

作者： Taouba Kaouther Jouini Zhiyong Sun Venkatraman Renganathan Veit Hagenmeyer Institute of Automation and Applied Informatics (IAI) at Karlsruhe Institute of Technology Germany Department of Electrical Engineering Eindhoven University of Technology Netherlands Department of Automatic Control LTH Lund University Sweden

We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set and the initial input lies on an ellipsoid inside the input constraint set, we show that the stabilizing controller solves the constrained optimal control problem. Compared to the state-of-the-art, we avoid solving nonlinear optimization problems evaluated pointwise, i.e., for every state, or in a repetitive fashion, i.e., at each time step. We apply our theoretical results to study the angular droop control studied in (Jouini et al., 2022) of an inverter-based power network. For this, we accommodate the constraints on the angle and power generation and exemplify our approach through a two-inverter case study.

关键词： Optimal Control Non-Linear Control Systems Networked Systems Power and Energy Systems

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On the Nuances of Multimodal Laughter Detection: Where, Why, and When Visual Insight Augments Audio in Classification

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IEEE Access 2025年 13卷 105246-105263页

作者： Liviu-Alexandru Marina Corina Dimitriu Department of Audio Research and Development Xperi Inc. San Jose CA USA Department of Automation and Applied Informatics Transilvania University of Braşov Braşov Romania Department of Computer Science Alexandru Ioan Cuza University Iaşi Romania

This paper explores the impact of visual input on traditional audio classification, focusing on the analysis of audiovisual data compilation and the interaction between modalities in laughter detection. While assessing user reactions to measure potential engagement is distinct from evaluating a content’s entertainment value, incorporating user-centered audio and visual cues enhances the contextual understanding of stimuli and the completeness of the emotional response. Among the results, making use of facial expressions augments the audio-only prediction accuracy with up to 26% when cross-attention mechanisms are employed. To evaluate the robustness of our proposed approach, experiments were systematically conducted under unimodal conditions, omitting each modality individually to assess its impact on performance. As audio and visual insights yield unbalanced contributions to the user’s overall emotional profiling, the accuracy gain of visual features on top of the audio setup provides evidence on the classifier’s ability to capture the nuances of human laughter behaviors.

关键词： Visualization Feature extraction Databases Neural networks Deep learning Annotations Accuracy Transformers Mel frequency cepstral coefficient Machine learning algorithms

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The Usability of Derived Function Features in Online Signature Verification

The Usability of Derived Function Features in Online Signatu...

引用

International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Cintia Lia Szucs Bence Kovari Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

Handwritten signatures are one of the most commonly used biometrics. Because signatures are widely accepted, their verification is a fundamental problem. The aim of signature verification is to decide about the origin of the signature so the ability to detect forgeries. Until offline signature verification is based on the scanned image of the signatures, online signature verification applies different electronic devices to capture the signatures. Online signatures also contain dynamic information such as the pressure or inclination angle of the pen, so it is much more challenging to forge online signatures than offline ones. In addition, it is possible to define and calculate further derived features based on the captured ones. The captured features are usually function features, which means they assign a value to each signature point or specified sets of signature points. This work aims to compare the usability of common derived function features using a dynamic time warping (DTW) based solution.

关键词： Databases Biometrics (access control) Forgery Usability Machine intelligence

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Validation of real-time simulation model of a three-phase Active-Front-End (AFE) rectifier

Validation of real-time simulation model of a three-phase Ac...

引用

International Youth Conference on Energetics (IYCE)

作者： MD Moshiur Rahman Chowdhury Zoltá n Sü tő Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9781665487214

ISBN: (纸本)9781665487221

Active rectifiers are commonly used converters in interfacing AC and DC grids due to their bidirectional power flow capabilities. Nowadays the development workflow of power converters includes real-time simulation steps to validate control concepts with hardware implementation in a safe environment. The paper presents the development process of a real-time HIL simulation framework for rapid-prototyping of advanced control algorithms of an Active-Front-End (AFE) rectifier. The control concepts and the main circuit models are realized in Matlab/Simulink and fitted for code-generation.

关键词： AC-DC power converters Codes Hardware-in-the-loop simulation Rectifiers Process control Bidirectional power flow Real-time systems

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COMPARING SPECTROSCOPY MEASUREMENTS IN THE PREDICTION OF IN VITRO DISSOLUTION PROFILE USING ARTIFICIAL NEURAL NETWORKS

arXiv

引用

arXiv 2022年

作者： Mrad, Mohamed Azouz Csorba, Kristóf Galata, Dorián László Nagy, Zsombor Kristóf Nagy, Brigitta Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

Dissolution testing is part of the target product quality that is essential in approving new products in the pharmaceutical industry. The prediction of the dissolution profile based on spectroscopic data is an alternative to the current destructive and time-consuming method. Raman and near-infrared (NIR) spectroscopies are two fast and complementary methods that provide information on the tablets' physical and chemical properties and can help predict their dissolution profiles. This work aims to compare the information collected by these spectroscopy methods to support the decision of which measurements should be used so that the accuracy requirement of the industry is met. Artificial neural network models were created, in which the spectroscopy data and the measured compression curves were used as an input individually and in different combinations in order to estimate the dissolution profiles. Results showed that using only the NIR transmission method along with the compression force data or the Raman and NIR reflection methods, the dissolution profile was estimated within the acceptance limits of the f2 similarity factor. Adding further spectroscopy measurements increased the prediction accuracy. © 2022, CC BY.

关键词： Dissolution

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Tuning of discrete-time angular droop controllers

Tuning of discrete-time angular droop controllers

引用

Control Technology and Applications (CCTA),

作者： Taouba Kaouther Jouini Zhiyong Sun Veit Hagenmeyer Institute of Automation and Applied Informatics (IAI) at Karlsruhe Institute of Technology Germany Department of Electrical Engineering Eindhoven University of Technology Netherlands

We study discrete-time angular-droop control in power inverter networks and leverage second-order information for the tuning. We thereby increase the rate of convergence of the closed-loop angle trajectories towards an induced steady state angle. In particular, we select the input penalty matrix, representing a tuning knob to be a sufficiently small diagonal matrix so that the closed-loop system approximately yields Newton’s method. In this way, we ensure quadratic convergence, a feat that is otherwise not achievable with a constant, sufficiently large diagonal input penalty matrix. This draws a link between second-order methods known for their quadratic rate of convergence and the tuning of inverse optimal stabilizing controllers for discrete-time integrator dynamics.

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