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International Conference on electrical engineering, Computing Science and automatic control (CCE)

作者： Mario Andrés Aguilar-Orduña Hebertt José Sira-Ramírez Brian Camilo Gómez-León Rubén Alejandro Garrido-Moctezuma Electrical Engineering Department Cinvestav-IPN Mexico City Mexico Automatic Control Department Cinvestav-IPN Mexico City Mexico

Technological advances have led to the development of smaller and more efficient satellites, which have gained popularity in various fields including education, research, and communications. However, disturbances such as gravitational forces, atmospheric drag, and space debris may affect their orbits. This article proposes a two-stage Active Disturbance Rejection control (ADRC) approach for the orbit transfer of small satellites. The paper presents the control design procedure and showcases numerical simulations, demonstrating the technique’s effectiveness in the particular case of study.

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Comparison of artificial intelligence algorithms and expert approach in risk classification in nephrology 4

Comparison of artificial intelligence algorithms and expert ...

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4th International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2024

作者： Pawuś, Dawid Paszkiel, Szczepan Porażko, Tomasz University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Prószkowska 76 Street Opole45-758 Poland Departament of Internal Medicine and Nephrology Institute of Medical Sciences University of Opole Oleska 48 Street Opole45-052 Poland Departament of Nephrology with Dialysis Unit Opole University Hospital Witosa 26 Street Opole46-020 Poland

This study presents a comparative analysis of various artificial intelligence (AI) and machine learning (ML) algorithms for risk classification in idiopathic membranous nephropathy (IMN), a complex kidney disease. The research evaluates seven different models, including K-Nearest Neighbors, Decision Trees, Random Forests, Support Vector Machines, Adaptive Boosting, LightGBM, and Multilayer Perceptron. The results reveal that ensemble methods, particularly Random Forests, achieve the highest precision in classifying IMN risk levels, highlighting their potential in improving diagnostic accuracy and patient management in nephrology. The study underscores the importance of model selection and fine-tuning to optimize AI applications in clinical settings, providing a basis for future advancements in AI-driven nephrology. © 2023 Copyright for this paper by its authors.

关键词： Expert systems

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Trajectory tracking of a single-link manipulator driven from a double-bridge Buck converter: A cascade ADRC approach.

Trajectory tracking of a single-link manipulator driven from...

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International Conference on electrical engineering, Computing Science and automatic control (CCE)

作者： Alejandro Esaú Meléndez Hernández Mario Andrés Aguilar-Orduña Brian Camilo Gómez-León Hebertt José Sira-Ramírez Electrical Engineering Department Cinvestav-IPN Mexico City Mexico Automatic Control Department Cinvestav-IPN Mexico City Mexico

The present article deals with a two-stage cascade ADRC control scheme applied to an actuated single manipulator mechanical system driven by a DC motor controlled by a double bridge DC-DC Buck converter. The proposal illustrates the advantages of the cascade schemes for SISO-coupled subsystems, where interconnected electrical and mechanical stages with different time constants are naturally separated. Experimental validations are shown where a trajectory-tracking task is proposed as a control objective. A simple but effective Exponential Moving Average filter proposal for the measurement noise management is included due to the noisy electrical signals used to control the internal cascade ADRC scheme.

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On Parameter Selection for First-Order Methods: A Matrix Analysis Approach 9

On Parameter Selection for First-Order Methods: A Matrix Ana...

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Baron-Prada, Eder Alsubaihi, Salman Alshehri, Khaled Albalawi, Fahad Austrian Institute of Technology Vienna1210 Austria Eth Zurich Automatic Control Laboratory Zürich8092 Switzerland Riyadh Saudi Arabia Control and Instrumentation Engineering Department Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics Kfupm Saudi Arabia College of Engineering Taif University Department of Electrical Engineering P.O. Box 11099 Taif21944 Saudi Arabia

ISBN: (纸本)9798350311402

First-order convex optimization algorithms are popular due to their computational attractiveness and applicability to a wide range of domains such as machine learning and control. Despite the substantial progress being made over the last few decades, some open questions related to their convergence remain unaddressed. In addition, majority of the first-order methods assume strong convexity to analyze both the stability of the method and derive an explicit convergence rate. In this manuscript, we relax the strong convexity condition, and then, lay out two main contributions. First, we provide a methodology where one can analyze the speed of convergence of the algorithm using the contractive theory and linear algebra. Second, we find explicit values of the tuning parameters of the Double Momentum Algorithm (which unifies many of the popular algorithms), ensuring stability for gradient L-Lipchitz functions. In this work, while an explicit convergence rate is not provided, the foundational results serve as a stepping stone in that direction, as we provide an explicit non-asymptotic rate. Furthermore, our numerical experiments demonstrate superior performance of the proposed method. Beyond optimization, we also apply our method to two-sided markets in non-cooperative game theory. © 2023 IEEE.

关键词： Machine learning

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Integrating Visual SLAM and Smooth Speed control for Realizing Real-Time Autonomous System

Integrating Visual SLAM and Smooth Speed Control for Realizi...

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International Conference on Computer and Automation engineering, ICCAE

作者： Mao-Jen Ko Yu-Chen Lin Chih-Hung Cheng Thanh-Tan Nguyen Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan

ISBN: (数字)9798350370058

ISBN: (纸本)9798350370164

In recent years, the rapid development of autonomous system technology has increasingly positioned it as a crucial player in modern transportation. Appropriate speed planning emerges as one of the key elements for achieving safe and efficient autonomous system operations. Speed planning not only requires adherence to road speed limits and ensuring safe distances to avoid collisions but also necessitates consideration for ensuring passenger comfort. This paper proposes a method that restricts acceleration and jerk to achieve smooth speed control, enabling autonomous system to emulate the driving style of human drivers. Utilizing visual SLAM for feature extraction and matching on images, a sparse point cloud three-dimensional map of the environment is constructed. The recorded path is tracked using the Pure Pursuit algorithm. Finally, this paper will validate the proposed approach through an embedded system deployed in a real vehicle. The integration of visual SLAM and smooth speed control technology realizes a real-time and smooth autonomous system, providing a safer autonomous system experience.

关键词： Point cloud compression Visualization Simultaneous localization and mapping Autonomous systems Velocity control Feature extraction Real-time systems

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Enabling IoT Continuous Connectivity in Smart Spaces 22

Enabling IoT Continuous Connectivity in Smart Spaces

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22nd International Symposium on Parallel and Distributed Computing, ISPDC 2023

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Batalla, Jordi Mongay Dobre, Ciprian Markakis, Evangelos Mastorakis, George University of Nicosia University of Nicosia Research Foundation Departement of Computer Science Nicosia Cyprus Warsaw University of Technology Warsaw Poland University Politehnica of Bucharest National Institute for Research and Development in Informatics Automatic Control and Computers Bucharest Romania Hellenic Mediterranean University Department of Electrical and Computer Engineering Heraklion Greece Hellenic Mediterranean University Department of Management Science and Technology Agios Nikolaos Greece

ISBN: (纸本)9798350341270

Smart spaces are a rapidly emerging concept in technology. They result from the convergence of various novel technologies, such as the Internet of Things, Machine Learning and Artificial Intelligence, which allow for greater levels of automation and control within physical environments. The devices which are connected to the IoT network are equipped with sensors to acquire and exchange data. As a result, the IoT has transformed how we live, work, and play. However, the deployment in smart spaces is not always the best due to the issues arising from network node positioning. Therefore, we are investigating solutions to this problem with a novel approach which utilises Voronoi diagrams in conjunction with the algorithmic genetic technique. First, the initial positions of the IoT nodes will be determined by simulating a homogeneous Poisson point process in the smart space environment. Then, after dividing the area into the Voronoi cells, the genetic algorithm will optimise the position towards achieving full network coverage within the smart space. Experimental results prove the 100% network coverage within the specified area. © 2023 IEEE.

关键词： Genetic algorithms

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A simplified pursuit-evasion game with reinforcement learning

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2021年第2期65卷 160-166页

作者： Paczolay, Gabor Harmati, Istvan Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics 2 Magyar Tudósok krt BudapestH-1117 Hungary

In this paper we visit the problem of pursuit and evasion and specifically, the collision avoidance during the problem. Two distinct tasks are visited: The first is a scenario when the agents can communicate with each other online, meanwhile in the second scenario they have to only rely on the state information and the knowledge about other agents' actions. We propose a method combining the already existing Minimax-Q and Nash-Q algorithms to provide a solution that can better take the enemy as well as friendly agents' actions into consideration. This combination is a simple weighting of the two algorithms with the Minimax-Q algorithm being based on a linear programming problem. © 2021 Budapest University of Technology and Economics. All rights reserved.

关键词： Reinforcement learning

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Analysis of Radio Frequency and Ultraviolet Signals Emitted by Surface Partial Discharges

Analysis of Radio Frequency and Ultraviolet Signals Emitted ...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Michał Kozioł Michał Kunicki Ireneusz Urbaniec Łukasz Nagi Ondrej Kabot Lukas Klein Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland ENET Centre VSB – Technical University of Ostrava Ostrava Czech Republic

Partial discharges (PD) occurring in high-voltage insulation systems can cause equipment failures and pose safety hazards. Commonly used techniques for detecting and characterizing PD activity, especially on the surface of insulation systems, include radio frequencies signal analysis and detection of ultraviolet radiation emissions. The aim of the research work was to perform a comparative analysis of the signals emitted by surface partial discharges in radio frequencies and the phenomena accompanying ultraviolet radiation emissions, as well as indicating possible directions for further basic research aimed at building a knowledge base and improving measurement methods. This paper presents an analysis of VHF, UHF and UV signals emitted by surface PD generated under laboratory conditions. The obtained results confirm that radio frequencies and UV signal analysis can provide important information about the activity and surface location of PD, including information on the intensity and nature of PD.

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Uncertainty-Aware Decision-Making and Planning for Autonomous Forced Merging

Uncertainty-Aware Decision-Making and Planning for Autonomou...

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IEEE Conference on Decision and control

作者： Jian Zhou Yulong Gao Björn Olofsson Erik Frisk Department of Electrical Engineering Division of Vehicular Systems Linköping University Linköping Sweden Department of Electrical and Electronic Engineering Imperial College London London United Kingdom Department of Automatic Control Lund University Lund Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we develop an uncertainty-aware decision-making and motion-planning method for an autonomous ego vehicle in forced merging scenarios, considering the motion uncertainty of surrounding vehicles. The method dynamically captures the uncertainty of surrounding vehicles by online estimation of their acceleration bounds, enabling a reactive but rapid understanding of the uncertainty characteristics of the surrounding vehicles. By leveraging these estimated bounds, a non-conservative forward occupancy of surrounding vehicles is predicted over a horizon, which is incorporated in both the decision-making process and the motion-planning strategy, to enhance the resilience and safety of the planned reference trajectory. The method successfully fulfills the tasks in challenging forced merging scenarios, and the properties are illustrated by comparison with several alternative approaches.

关键词： Uncertainty Simulation Decision making Merging Estimation Robustness Trajectory Safety Planning Resilience

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Uncertainty-Aware Decision-Making and Planning for Autonomous Forced Merging

arXiv

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arXiv 2024年

作者： Zhou, Jian Gao, Yulong Olofsson, Björn Frisk, Erik Division of Vehicular Systems Department of Electrical Engineering Linköping University Linköping Sweden Department of Electrical and Electronic Engineering Imperial College London London United Kingdom Department of Automatic Control Lund University Lund Sweden

关键词： Motion planning

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