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arXiv 2024年

作者： Bouška, Michal Šůcha, Přemysl Novák, Antonín Hanzálek, Zdeněk Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Jugoslávských partyzánů 1580/3 Prague Czech Republic Czech Technical University in Prague Faculty of Electrical Engineering Department of Control Engineering Karlovo náměstí 13 Prague Czech Republic

In this paper, we investigate the use of the deep learning method for solving a well-known NP-hard single machine scheduling problem with the objective of minimizing the total tardiness. We propose a deep neural network that acts as a polynomial-time estimator of the criterion value used in a single-pass scheduling algorithm based on Lawler's decomposition and symmetric decomposition proposed by Della Croce et al. Essentially, the neural network guides the algorithm by estimating the best splitting of the problem into subproblems. The paper also describes a new method for generating the training data set, which speeds up the training dataset generation and reduces the average optimality gap of solutions. The experimental results show that our machine learning-driven approach can efficiently generalize information from the training phase to significantly larger instances. Even though the instances used in the training phase have from 75 to 100 jobs, the average optimality gap on instances with up to 800 jobs is 0.26%, which is almost five times less than the gap of the state-of-the-art heuristic. © 2024, CC BY-NC-ND.

关键词： Scheduling algorithms

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ATDN vSLAM: An All-Through Deep Learning-Based Solution for Visual Simultaneous Localization and Mapping

arXiv

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arXiv 2022年

作者： Szántó, Mátyás Bogár, György Richárd Vajta, László Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics 2 Magyar tudosok Blvd. BudapestH-1117 Hungary

In this paper, a novel solution is introduced for visual Simultaneous Localization and Mapping (vSLAM) that is built up of Deep Learning components. The proposed architecture is a highly modular framework in which each component offers state of the art results in their respective fields of vision-based Deep Learning solutions. The paper shows that with the synergic integration of these individual building blocks, a functioning and efficient all-through deep neural (ATDN) vSLAM system can be created. The Embedding Distance Loss function is introduced and using it the ATDN architecture is trained. The resulting system managed to achieve 4.4% translation and 0.0176 deg/m rotational error on a subset of the KITTI dataset. The proposed architecture can be used for efficient and low-latency autonomous driving (AD) aiding database creation as well as a basis for autonomous vehicle (AV) control. © 2022, CC BY.

关键词： Autonomous vehicles

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Integrated Learning in electrical and control engineering Using an Educational Elevator System 11

Integrated Learning in Electrical and Control Engineering Us...

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11th International Conference and Exposition on electrical And Power engineering, EPE 2020

作者： Lucache, Dorin-Dumitru Gabor, Georgel Dosoftei, Constantin-Catalin Gheorghe Asachi' Technical University of Iasi Faculty of Electrical Eng. Energy and Applied Informatics Iasi Romania Gheorghe Asachi' Technical University of Iasi Faculty of Automatic Control and Computer Engineering Iasi Romania

ISBN: (纸本)9781728181264

The research of the authors is focused on presenting a practical multidisciplinary experiment-An elevator simulator to relate theory and practice inside of a lot of disciplines and to bring the 'real world' into a useful case study for electrical and control engineering education. Through the existence of interesting experiments, students gain motivation either to continue thinking and improving new solutions for building and control of elevators. The concept of the modern elevator is presented in this paper from the perspective of integration of current technological equipment like a programmable logic controller, inverter, encoder, human-machine-interface on which students can develop various control strategies using a SCADA system. The paper presents the some exercises that students can perform on the existent simulator. © 2020 IEEE.

关键词： engineering education

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Globally Optimal Online Redundancy Resolution for Serial 7-DOF Kinematics Along SE(3) Trajectories

Globally Optimal Online Redundancy Resolution for Serial 7-D...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Gerold Huber Dirk Wollherr Chair of Automatic Control Engineering (LSR) Faculty of Electrical Engineering Technical University of Munich München Germany

Redundant robots offer the possibility of improving agility, compared to their non-redundant counterparts, by exploiting the additional kinematic DOFs to increase a measure called manipulability. While it is common to maximize the manipulability measure during redundancy resolution locally, global optimization of a full trajectory is usually computationally too expensive and thus only considered for offline procedures in current literature. However, local maximization is prone to be sub-optimal and at times even fails at preserving agility of a robot that ought to be reactive. In this work we build upon our previous contributions on online trajectory generation on SE(3) and closed-form task space manipulability of a 7-DOF serial robot, and combine it with graph search techniques for global optimization. This enables, for the first time, online trajectory generation with globally optimal redundancy resolution regarding manipulability, to maintain agility in reactive robot behavior.

关键词： Automation Current measurement Conferences Redundancy Kinematics End effectors Trajectory

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Comparison of game theoretical strategy and reinforcement learning in traffic light control

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Periodica Polytechnica Transportation engineering 2020年第4期48卷 313-319页

作者： Guo, Jian Harmati, István Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics H-1521 P. O. B. 91 Budapest Hungary

Many traffic models and control methods have already been utilized in the public transportation system due to the increasing traffic congestion. Thus, an intelligent traffic model is formalized and presented to control multiple traffic light simultaneously and efficiently according to the distribution of vehicles from each incoming link (i.e. sections) in this paper. Compared with constant strategy, two methods are proposed for traffic light control, i.e., game theoretical strategy and reinforcement learning methods. Game theoretical strategy is generated in a game theoretical framework where incoming links are regarded as players and the combination of the status of traffic lights can be regarded as decisions made by these players. The cost function is evaluated and the strategy is produced with Nash equilibrium for passing maximum vehicles in an intersection. The other one is Single-Agent Reinforcement Learning (SARL), specifically with the Q-learning algorithm in this case, which is usually used in such a dynamic environment to control traffic flow so the traffic problem could be improved. Generally, the intersection is regarded as the centralized agent and controlling signal status is considered as the actions of the agent. The performance of these two methods is compared after simulated and implemented in a junction. © 2020 Budapest University of Technology and Economics. All rights reserved.

关键词： Game theory

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Optimization of Methodology for Identifying Partial Discharges in Insulating Liquids Through Optical Radiation Analysis Using Machine Learning

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Michał Kozioł Tomasz Boczar Daniel Jancarczyk Marcin Bernaś Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science and Automatics University of Bielsko-Biala Bielsko-Biala Poland

The emission of optical radiation is associated with electrical discharges in high-voltage power systems. Detecting, measuring, and analyzing this radiation can enable the identification of the type of electrical discharge and the determination of its source. This article presents the results of measurements and analysis of optical spectra in the context of their application for recognizing different forms of electrical discharges in selected insulating liquids. Optical radiation in the ultraviolet, visible light, and near-infrared range, emitted by electrical discharges in insulating liquids commonly used in electrical engineering, such as mineral oil, natural ester, and synthetic ester, was analyzed. As part of the research, an innovative methodology for measuring and analyzing optical radiation emitted by electrical discharges was proposed, utilizing machine learning (ML) tools for precise analysis and interpretation of measurement data. The research results enrich current knowledge with new parameters and measurement indicators, representing another stage in the development of diagnostic methods that can be used to build expert systems and new diagnostic techniques for high-voltage insulation systems.

关键词： Stimulated emission Optical variables measurement Optical fibers Optical sensors Optical fiber sensors Partial discharges electrical engineering Signal processing algorithms Optical films Discharges (electric)

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A Brief Review of Unmanned Underwater Vehicle Human-Machine Interaction

A Brief Review of Unmanned Underwater Vehicle Human-Machine ...

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IEEE International Conference on Underwater System Technology: Theory and Applications (USYS)

作者： A. F. Ayob M. R. Arshad S. Jamaludin S.Z.A. Syed Ahmad Virtual Simulator Group (VSG) Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia Underwater Control & Robotics Group (UCRG) School of Electrical & Electronic Engineering Engineering Campus Universiti Sains Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia

Unmanned Underwater Vehicle (UUV) research typically seeks to understand the physical performance and control aspects of the underwater vessel operated in a dynamic environment. Commonly, UUV operations involve highly orchestrated coordination to conduct surveys, maintenance, and repair missions. With the vast selection of UUV products in the market, the disparity in the standard user interface is evident. Despite the high-risk and critical operations faced by the UUV operators, very little focus has been dedicated to reviewing the human-UUV interface aspect of the operations of UUV. In this review, an area of Human Machine Interaction (HMI), within the perspective of UUV designs is discussed.

关键词： Human computer interaction Autonomous underwater vehicles Maintenance engineering Vehicle dynamics Standards

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Optimal Multi-Target Path Planing control for Multiple Mobile Robot System

Optimal Multi-Target Path Planing Control for Multiple Mobil...

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International Conference on System Science and engineering (ICSSE)

作者： Van-Phong Vu Tu-Gia-Thinh Nguyen Xuan-Sang Nguyen Van-Tung Le Van-Thuyen Ngo Duc-Hung Pham Hoang Kim Uyen Department of Automatic Control Ho Chi Minh city University of Technology and Education Ho Chi Minh city Vietnam Faculty of Electrical and Electronic Engineering Hung Yen University of Technology and Education Hung Yen Vietnam Faculty of Electronics and Telecommunication Engineering Da Nang University of Science and Technology Da Nang Vietnam

In this paper, the problems related to cooperative control for the multiple mobile robot system (MMRS) is presented. The LIDAR sensor is employed to obtain the 2D map of the indoor space. The formation control and the leader-following algorithm are applied to control the MMRS moving in a specific formation. Additionally, this paper considers the scenario that the MMRS has to move to several targets in the indoor space with many obstacles. Therefore, the indoor travelling salesman problem-based Ant Colony Optimization (ACO) is studied in this work to determine the optimal moving path of the MMRS. To prove the effectiveness and merit of the proposed methods, the simulation results are provided in this article.

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Thermal Images Based Mobile Application for Identifying Faults in Photovoltaics Modules

Thermal Images Based Mobile Application for Identifying Faul...

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International Symposium on Fundamentals of electrical engineering (ISFEE)

作者： Alexandru-Ionel Constantin Ramona-Nicoleta Banaseanu Paula Anghelita Gabriela Iosif Dorian Marin Department of Renewable Resources and Energy Efficiency National Institute for Research & Development in Electrical Engineering ICPE-CA Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Faculty of Electronics Telecommunications and Information Technology National University of Science and Technology POLITEHNICA Bucharest Office of Management for Knowledge and Information National Institute for Research & Development in Electrical Engineering ICPE-CA

ISBN: (数字)9798350308563

ISBN: (纸本)9798350308570

The paper describes few faults that can be present in Photovoltaic modules and presents results related to training and the testing of a mobile application designed for identifying faults in photovoltaic modules based on thermal images. The mobile application was trained and then tested with different individual and multiple faults. The mobile application can identify with high accuracy both the individual and multiple faults if the thermal images are preprocessed before to be uploaded for analysis.

关键词： Fault diagnosis Training Temperature distribution Temperature dependence Accuracy Thermal engineering Mobile applications

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Non-Holonomic RRT & MPC: Path and Trajectory Planning for an Autonomous Cycle Rickshaw

arXiv

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arXiv 2021年

作者： Bojadžić, Damir Kunze, Julian Osmanković, Dinko Malmir, Mohammadhossein Knoll, Alois Germany Department of Automatic Control and Electronics Faculty of Electrical Engineering University of Sarajevo Bosnia and Herzegovina Germany

This paper presents a novel hierarchical motion planning approach based on Rapidly-Exploring Random Trees (RRT) for global planning and Model Predictive control (MPC) for local planning. The approach targets a three-wheeled cycle rickshaw (trishaw) used for autonomous urban transportation in shared spaces. Due to the nature of the vehicle, the algorithms had to be adapted in order to adhere to non-holonomic kinematic constraints using the Kinematic Single-Track Model. The vehicle is designed to offer transportation for people and goods in shared environments such as roads, sidewalks, bicycle lanes but also open spaces that are often occupied by other traffic participants. Therefore, the algorithm presented in this paper needs to anticipate and avoid dynamic obstacles, such as pedestrians or bicycles, but also be fast enough in order to work in real-time so that it can adapt to changes in the environment. Our approach uses an RRT variant for global planning that has been modified for single-track kinematics and improved by exploiting dead-end nodes. This allows us to compute global paths in unstructured environments very fast. In a second step, our MPC-based local planner makes use of the global path to compute the vehicle’s trajectory while incorporating dynamic obstacles such as pedestrians and other road users. Our approach has shown to work both in simulation as well as first real-life tests and can be easily extended for more sophisticated behaviors. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control

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