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2023 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2023

作者： Merzlikina, Elena Sviridov, Georgiy Farafonov, Georgiy Moscow Power Engineering Institute National Research University Dept. of Automated Control Systems for Thermal Processes Moscow Russia

ISBN: (纸本)9781665475952

This paper considers in general the problem of control system performance improvement, and, particularly, using predictive control systems. Various ways of improvement are described and the predictive system is considered in detail. This system is implemented in a laboratory workbench equipped with a physical model of an electric heater and a modern PLC. The system consists of a PID-algorithm, a prediction module and an auto-tuning module. The prediction algorithm is linear. The auto-tuning module allows to refresh the plant model and to re- tune the PID-algorithm if necessary. The possibility to implement the control system described using a modern PLC is estimated and the performance of this system is analyzed. Influence of the prediction time value is analyzed and recommendation on the prediction time value selection is given. © 2023 IEEE.

关键词： Forecasting

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Contagion Propagation with Rule-Based Reasoning and Decentralized control in an Agent-Based Susceptible-Infected-Recovered-Susceptible Infodemic Model 8

Contagion Propagation with Rule-Based Reasoning and Decentra...

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8th International Conference on Big Data, Knowledge and control systems engineering, BdKCSE 2023

作者： Berceanu, Cristian Arshad, Nadia Patrascu, Monica University Politehnica of Bucharest Complex Systems Laboratory Dept. of Automatic Control and Systems Engineering Bucharest Romania University of Bergen Section for Epidemiology and Medical Statistics Dept. of Global Public Health and Primary Care Bergen Norway University Politehnica of Bucharest Complex Systems Laboratory Romania University of Bergen Centre for Elderly and Nursing Home Medicine Dept. of Global Public Health and Primary Care Bergen Norway

ISBN: (纸本)9798350313246

In recent years, and especially during the on-going pandemic, the interest in investigating the dynamics of infodemics has increased to unprecedented levels. In this study we propose an agent-based model for the spread of misinformation, disinformation, and other similar information. The model is based on the susceptible-infected-recovered-susceptible epidemic interpretation. We introduce a rule-based reasoning module to model individual bias in the perception of information based on the psychology concept of illusion of knowledge. We integrate this module into a deliberative-reactive agent controller structure and a decentralized control scheme for the multi-agent system. Results show significant differences between the outputs of the proposed model and the classical version, impressing on the effects of considering local agent individuality when modeling human psycho-social interactions. © 2023 IEEE.

关键词： Multi agent systems

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Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry 5

Monitoring and Forecasting Quality Indicators of Predough Pr...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Lutska, Nataliia Zaiets, Nataliia Vlasenko, Lidiia Zhyltsov, Andrii Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Electromagnetic Systems The Institute of Electrodynamics The National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350384499

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them. ©2024 IEEE.

关键词： Bakeries

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Iterative Robust Experiment Design for MIMO System Identification via the S-Lemma

Iterative Robust Experiment Design for MIMO System Identific...

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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Dirkx, Nic Tiels, Koen Oomen, Tom Asml Veldhoven Netherlands Eindhoven University of Technology Control Systems Technology Dept. of Mechanical Engineering Eindhoven Netherlands Eindhoven University of Technology Control Systems Technology Section Department of Mechanical Engineering Eindhoven Netherlands Delft University of Technology Delft Center for Systems and Control Delft Netherlands

ISBN: (纸本)9798350335446

Optimal input design plays an important role in system identification for complex and multivariable systems. A known paradox in input design is that the optimal inputs depend on the true but unknown system. The aim of this paper is to design inputs for multivariable systems that are robust to all system variations within a given continuous uncertainty set. In the presented approach, the robust design problem is cast as an infinite-dimensional min-max optimization problem, and tackled via the S-lemma in an iterative approximation scheme. Experimental results from a multivariable motion system show that the algorithm enables significant robustness improvements. © 2023 IEEE.

关键词： Iterative methods

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Circuit Design Method of Rate Increase in Operational Amplifiers Based on the MH2XA031 Array Chip and CBJT Technological Routes

Circuit Design Method of Rate Increase in Operational Amplif...

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IEEE NW Russia Young Researchers in Electrical and Electronic engineering Conference (EIConRusNW)

作者： Alexey E. Titov Dmitriy V. Kleimenkin Nikolay N. Prokopenko dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia dept. of Scientific Research dept. of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

It has been revealed that in the conditions of small-scale production of discrete-analog filters on switched capacitors and ADC-drivers, it is most advisable to design high-speed operational amplifiers (OAs) based on the CBJT technological route and the MH2XA031 array chip, which allows operation in conditions of low temperatures and exposure to radiation. It has been established that most commercially produced $O A s$ provide an average value of the slew rate (SR, up to $200 \div 300 \mathrm{~V} / \mu \mathrm{s}$). This is largely due to the limitations of the technologies used, and most importantly, to the irrational design of circuits. We study the maximum performance parameters of a CBJT OA with one integrating capacitor, which ensures the stability of the $O A$, and a differentiating transient correction circuit, which is implemented by connecting additional small capacitors to the original circuit. In this case, the $S R$ of the $O A$ increases by more than 500 times (up to $4000 \mathrm{~V} / \mu \mathrm{s}$).

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Methods for Developing Effective Models of Biomedical Processes in MATLAB 17

Methods for Developing Effective Models of Biomedical Proces...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer engineering, TCSET 2024

作者： Kolisnyk, Kostyantyn Kolisnyk, Viktoriia Wik, Torsten National Technical University 'Kharkiv Polytechnic Institute' Dept. Industrial and Biomedical Electronics Kharkov Ukraine Kharkiv National University of Radio Electronics Dept. Media Engineering and Information Radioelectronic Systems Kharkiv Ukraine Institutionen for elektroteknik Chalmers tekniska hogskola Dept. Systems and Control Technology Electrical Technology Gothenburg Sweden

ISBN: (纸本)9798331520564

Mathematical modeling in the study of dynamic processes in biomedicine is currently widely used. The use of mathematical statistics and formal logic methods in the analysis of complex biomedical processes is especially important for increasing the efficiency of biomedical research. Taking into account the established growth of the technical base of research, the development of new technologies and technical means for obtaining and processing statistical biomedical information, the use of mathematical modeling methods is a fairly promising direction in scientific and practical work. In this paper the authors studies the possibility of improving the quality of biomedical process modeling using the MATLAB software environment. The research was carried out on real statistical material obtained by the authors during a full-scale experiment to study the impact of a complex of external factors on patients. The results obtained in this work can be used in the implementation of scientific and applied research of biomedical processes. © 2024 IEEE.

关键词： MATLAB

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Speech Emotion Recognition Using Deep Learning

Speech Emotion Recognition Using Deep Learning

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International Conference on Soft Computing and Measurements (SCM)

作者： Mohamed A. Gismelbari Ilya I. Vixnin Gregory M. Kovalev Eugane E. Gogolev Dept. of Automatic Control Systems Saint Petersburg Electrotechnical University “LETI” Saint Petersburg Russia

ISBN: (数字)9798350363708

ISBN: (纸本)9798350363715

This study explores the application of deep learning techniques in recognizing emotional states from spoken language. Specifically, we employ Convolutional Neural Networks (CNNs) and the HuBERT model to analyze the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). Our findings suggest that deep learning models, particularly the HuBERT model, exhibit significant potential in accurately identifying speech emotions. The models were trained and tested on a dataset containing various emotional expressions, including happiness, sadness, anger, and fear, among others. The experimentation involved preprocessing the audio data, feature extraction using Mel Frequency Cepstral Coefficients (MFCCs), and implementing deep learning architectures for emotion classification. The HuBERT model, with its advanced self-supervised learning mechanism, outperformed traditional CNNs in terms of accuracy and efficiency. This research highlights the importance of selecting appropriate deep learning models and feature sets for the task of speech emotion recognition. Our analysis demonstrates that the HuBERT model, by leveraging contextual information and temporal dynamics in speech, offers a promising approach for developing more sensitive and accurate SER systems. These systems have potential applications in various fields, including mental health assessment, interactive voice response systems, and educational software, by enabling machines to understand and respond to human emotions more effectively. The findings of this study contribute to the ongoing discussion in the field of artificial intelligence about the best practices for implementing deep learning techniques in speech processing tasks.

关键词： Deep learning Analytical models Emotion recognition Accuracy Training data Speech recognition Data models

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Power Loss Analysis of Energy Management System with Model Predictive control in Mae Hong Son Microgrid 3

Power Loss Analysis of Energy Management System with Model P...

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3rd IEEE International Conference on Power Electronics, Intelligent control and Energy systems, ICPEICES 2024

作者： Prapanwattana, Nattakit Dechawatanapaisal, Donlapat Banjerdpongchai, David Rajan, Abhishek Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Faculty of Engineering Dept. of Electrical Engineering 254 Phayathai Rd Bangkok Pathumwan10310 Thailand National Institute of Technology Sikkim Dept. of Electrical Engineering South Sikkim Ravangla737139 India

ISBN: (纸本)9798350387193

Energy management system (EMS) is an important tool for energy efficiency and reliability of the power system. The optimal power dispatch of energy resources can be obtained using the nonlinear model predictive control (NMPC). It is formulated as an optimization problem subject to linear and nonlinear constraints. Although the existing system works well under the current conditions, power loss has not been considered. Power loss in transmission lines occurs due to their resistance and a high amount of power flow to loads connecting to the system. The power loss leads to decreased efficiency in the electrical system and reduces the lifespan of equipment because of the high temperature from loss. This paper aims to analyze the power loss in the Mae Hong Son (MHS) microgrid. To achieve the research objectives, we employ the EMS of MHS with NMPC and calculate power loss in transmission lines for a period of 7 days. EMS considers three objective functions, namely, total operating cost, total carbon dioxide emission, and combined economic and emission dispatch and take into account of three seasons consisting of rainy, winter, and summer. © 2024 IEEE.

关键词： Predictive control systems

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Assessment of the Reliability of the Model of an Unmanned Underwater Vehicle

Assessment of the Reliability of the Model of an Unmanned Un...

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2022 Conference of Russian Young Researchers in Electrical and Electronic engineering, ElConRus 2022

作者： Neuimin, German A. Sakovich, Sergey Yu. Galtsov, German A. Saint Petersburg State Marine Technical University Smtu Dept. of Automatic Control Systems and On-Board Computing Saint Petersburg Russia

ISBN: (纸本)9781665409933

关键词： Submersibles

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Tube-based coalitional MPC with plug-and-play features

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IFAC-PapersOnLine 2023年第2期56卷 7704-7709页

作者： E. Masero P.R. Baldivieso-Monasterios J.M. Maestre P.A. Trodden E.F. Camacho Dept. of Ingeniería de Sistemas y Automática Universidad de Sevilla Spain Dept. of Automatic Control and Systems Engineering University of Sheffield UK Dept. of Systems Science Graduate School of Informatics Kyoto University Japan

This paper presents a distributed setting of model predictive control (MPC) to manage linear multi-agent systems consisting of coupled subsystems. Specifically, local controllers can work in coalitions to improve performance and handle plug-and-play events. This study provides insight into a coalitional MPC strategy based on optimized tubes that handles plug-in and plug-out subsystems. Moreover, we explore an inherent robustness gap to absorb disturbances not covered by the tubes without having to group local controllers. A comparison of our approach with centralized and decentralized MPC is reported using an illustrative example.

关键词： Model predictive control distributed control multi-agent systems time-varying systems robust control plug-and-play events

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