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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2024年第3期86卷 67-80页

作者： Colbu, Ștefania-Cristiana Băncilă, Daniel-Marian Petrescuniță, Alina Popescu, Dumitru Olteanu, Severus-Constantin Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Mathematical Methods and Models National University of Science and Technology POLITEHNICA Bucharest Romania

The present paper introduces a comparative analysis of the management of a stochastic optimization problem using both a risk deterministic approach and a support vector machine strategy. This optimization problem is formulated in consideration of the influence produced by environmental factors, such as irradiance and temperature, on a photovoltaic panel. The problem will be solved by applying both methods to determine the Maximum Power Point (MPP), thereby to enhance the power generation efficiency. The primary objective is to conduct an analysis comparing the two approaches, with the aim of recommending the most suitable approach for Maximum Power Point Tracking (MPPT). © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： machine learning photovoltaics risk optimization support vector machine for regression

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AN INTEGRATED BREAST CANCER MICROARRAY ANALYSIS APPROACH

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2022年第2期84卷 79-90页

作者： Lixandru-Petre, Irina-Oana Buiu, Catalin Dept. of Automatic Control and Systems Engineering University POLITEHNICA of Bucharest Romania

As knowledge of the biological and biophysical basis of cellular function has increased, opportunities to understand the cellular and molecular functioning of organic matter have expanded, and gene expression microarrays have become a widely used technique to study the dynamics of biological processes. In this paper, we present a gene expression analysis approach using R programming, starting from mRNA oligonucleotide matrices ending with interrelated genes, analyzed within a chosen biological process. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Microarrays

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Synthesis of Neural Network Program control Based on Pontryagin's Maximum Principle 8

Synthesis of Neural Network Program Control Based on Pontrya...

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8th International Conference on Information, control, and Communication Technologies, ICCT 2024

作者： Kozyr, Andrey Feofilov, Sergey Khapkin, Dmitry Tula State University Dept. of Automatic Control Systems Tula Russia

ISBN: (纸本)9798331517564

This paper solves the problem of synthesizing optimal control for complex nonlinear dynamic objects. Such problems often arise in various engineering applications such as robotics, mechatronics, and aerospace. Examples of such problems include the computation of the optimal flight path of an aircraft, manipulator control, and control of industrial applications. In most real-world applications, the control object is a high-order nonlinear dynamical system, and the parameters may be uncertain or vary over *** and iterative methods of optimal control synthesis are known;however, such methods are not applicable in the case of high dimensionality of the object "curse of dimensionality"and have poor convergence. In this paper, a new approach to solving the problem of program control synthesis based on the use of neural network controller is proposed. The loss function is formulated based on an adapted set of necessary optimality conditions derived from the maximum principle and approximation of the Hamilton-Jacobi-Bellman equation using neural networks. Compared to direct iterative methods, the method presented in this paper can efficiently obtain control from the state-space domain. The demonstration of the proposed method is carried out on a model example of constructing the optimal control of the output to the unstable position of the inverse pendulum, and the results of numerical simulation are given. The research was carried out at the expense of the grant of the Russian Science Foundation No. 23-29-00609, https://***/project/23-29-00609. © 2024 IEEE.

关键词： Flight paths

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Assessing Uncertainty in Space Weather Forecasting Using Quantile Regression and Complex Nonlinear systems Identification Techniques 6

Assessing Uncertainty in Space Weather Forecasting Using Qua...

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6th International Conference on Computing, Electronics and Communications engineering, iCCECE 2023

作者： Wei, Hua-Liang Balikhin, Michael A. Boynton, Richard J. Walker, Simon N. The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340921

Space weather forecasting is of global interest, and its importance is well established in research community and recognized by government, industries and stockholders. Over the past years, many types of predictive models have been developed in the literature. There is a general agreement that forecasting models should not only provide point prediction but also inform the uncertainty associated with the prediction. This study presents a novel method bases on quantile regression and complex dynamic modelling for measuring uncertainties in space weather forecasting. The approach is implemented using Quantile regression and Nonlinear AutoRegressive Moving Average with Exogenous inputs (NARMAX) methods (for short the approach is called Q-NARMAX). The method is applied to Disturbance storm index (Dst) observations to examine its interpretability and capability for uncertainty analysis. Results show that the proposed Q-NARX model can produce excellent predictions of the Dst index, and meanwhile provides a measure for assessing the uncertainty in the forecast. The innovative integration of quantile regression, complex dynamic modelling and nonlinear system identification techniques enables the proposed work to have following attractive advantages and properties: 1) it can produce excellent prediction accuracy for space weather forecasting, 2) it uses transparent models to approximate (represent) black-box systems, enabling to interpret the dependent relationship between space weather indices (system outputs) and their drivers (system inputs), and 3) more importantly, it allows for uncertainty assessment and analysis of models and forecasts. © 2023 IEEE.

关键词： Uncertainty analysis

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BIOPHYSICAL SIGNAL PROCESSING FOR automatic ANXIETY CLASSIFICATION IN A VIRTUAL REALITY EXPOSURE THERAPY SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2024年第2期86卷 73-84页

作者： Jinga, Nicolae Petrescu, Cătălin-Dumitru Mitruț, Oana Moldoveanu, Alin Moldoveanu, Florica Petrescu, Livia Dept. of Computer Science National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Faculty of Biology University of Bucharest Romania

This paper presents a signal processing framework for automatic anxiety level classification in a virtual reality exposure therapy system. Two types of biophysical data (heart rate and electrodermal activity) were recorded, pre-processed and passed through a feature extraction procedure that provided input for the real-time anxiety level classification algorithm. We showcase the mathematical and engineering techniques behind the procedures and conclude with the challenges encountered in our research and future development ideas. The proposed method provides a good estimate of the level of anxiety while having at the same time a reduced level of complexity, allowing implementation on equipment with limited computing resources. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Classification (of information)

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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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2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

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

ISBN: (纸本)9798350360646

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 ~V / μ 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 ~V / μ s). © 2024 IEEE.

关键词： array chip CBJT operational amplifier slew rate

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Speech Emotion Recognition Using Deep Learning 27

Speech Emotion Recognition Using Deep Learning

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27th International Conference on Soft Computing and Measurements, SCM 2024

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

ISBN: (纸本)9798350363708

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. © 2024 IEEE.

关键词： Convolution

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Features of Synthesis of Neural Network Simulators with Limiters 5

Features of Synthesis of Neural Network Simulators with Limi...

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5th International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Feofilov, Dmitry Khapkin, Dmitry Tula State University Dept. of Automatic Control Systems Tula Russia

ISBN: (纸本)9798350309126

One of the problems of the modern theory of automatic control is the construction of verified mathematical models of objects of regulation. In some cases, obtaining such models is not possible. This paper discusses approaches to the use of neural networks as regulators. Due to the presence of the adaptivity property, neuroregulators in some cases show a better quality of control in comparison with classical ones. The most common architectures of neural networks and methods of their training are considered. A comparative analysis was carried out. The first stage in the design of neural network regulators is the creation of a neuroimitator. An example of the synthesis of a neural network simulator is given. The proposed scheme has been worked out on systems with saturation type limiters and a mechanical stop. © 2023 IEEE.

关键词： Recurrent neural networks

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Synthesis of Neural Network Compensation of an Autonomous Electro-Hydraulic Actuator Based on a Sliding Mode control 7

Synthesis of Neural Network Compensation of an Autonomous El...

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7th International Conference on Information, control, and Communication Technologies, ICCT 2023

作者： Kozyr, Andrey Feofilov, Sergey Khapkin, Dmitry Tula State University Dept. of Automatic Control Systems Tula Russia

ISBN: (纸本)9798350340945

Autonomous electro-hydraulic actuators (AEHA) are widely used in industrial applications such as mobile manipulators, robotic exoskeleton, aerospace applications. AEHA has a number of significant advantages in relation to the electric drive: a high ratio of the developed force to the weight of the drive, compact dimensions of the autonomous drive, which are provided by the integrated layout of all elements of the electro-hydraulic system. However, the control of such systems becomes much more complicated due to the presence of significant nonlinearities in the control object. These include the non-linear characteristic of the switchgear, dry friction, and hard mechanical stops. All this makes it difficult to implement a control system based on classical controllers. The paper proposes a technique for synthesizing a controller that provides a sliding mode with compensatory neural network control for objects with an indefinite static characteristic. Using the direct Lyapunov method, we prove the stability of a feedback system. Numerical simulation results are presented to demonstrate the effectiveness of the proposed approaches. The study was supported by the Russian Science Foundation grant No. 23-29-00609, https://***/project/23-29-00609 © 2023 IEEE.

关键词： Lyapunov functions

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The Root-Mean-Square Velocity Stabilization of Swarm Multicopters Interacted by the Thermal Motion Equivalent Method 7

The Root-Mean-Square Velocity Stabilization of Swarm Multico...

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7th International Conference on Information, control, and Communication Technologies, ICCT 2023

作者： Heiss, Ed Kozyr, Andrey Morozov, Oleg Tula State University Dept. of Automatic Control Systems Tula Russia

ISBN: (纸本)9798350340945

The paper considers the problem of designing a regulator for a multicopter agent. Swarm control is organized by the thermal motion equivalent method. The idea of the method is the organization of the swarm agents' behavioral similarity to the atoms' thermal motion. This method makes it quite easy to organize the swarm agents' interaction and effectively solve problems: exploration issue in unknown environment, formation, tracking an object, mutual positioning of swarm agents. The key problem with the thermal motion equivalent method is the stabilization of the multicopter RMS velocity over time. Spontaneous growth or decrease in the agents' speed can lead to loss of swarm system controllability and mission failure. The paper proposes to synthesize a control system based on a linearized quadcopter model, which provides positional test oscillation stability of the aircraft to solve the above problem. The static state controller synthesized by the LMI method is used. Nonlinear model motion numerical simulation of a single UAV in a closed space is carried out in the paper. The results show the undamped multicopter oscillations. Multiple quadcopters are simulated in a confined space. The results show that the RMS agents' velocity does not change over time, which was required. © 2023 IEEE.

关键词： Stabilization

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