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International Scientific Conference on Electric Power engineering (EPE)

作者： Przemyslaw Krupiarz Jaroslaw Zygarlicki Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

This paper presents an initial study of Wireless Power Transfer systems design for Industrial Mobile Robots. Prerequisite for all industrial applications is that it shall be able to perform constantly, whereas currently the Industrial Mobile Robots must stop at fixed location to charge batteries. The time that robots are unutilized therefore should be minimized, to which we propose possible solutions. The designs apply an additional, intermediate energy buffer that increases the maximum applicable current. The proposed systems are split in two categories based on location, the first is a fixed, stationary type and the second is a type of phased array system built-in the plant floor.

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Automated Machine Learning Evaluation of Squat Movement Patterns Using Smartphone and CoreML

Automated Machine Learning Evaluation of Squat Movement Patt...

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IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications

作者： Marta Sokolowska Michal Podpora Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

There is a vast diversity of Machine Learning use cases, and both the hardware and the methodology itself are constantly getting better. This article presents a very specific use case – the recognising, classifying, and evaluation of human physical activity by using just a video stream from a smartphone and potentially instructing people how to exercise to get better results. The paper presents two key aspects of the challenge: (1) defining the problem in the physical activity domain and choosing a proper ML approach and tool, and (2) conducting the experiment using consumer-grade hardware (a smartphone) to evaluate if the proposed methodology is applicable using an easy-to-use tool and widely accessible hardware for users with limited (or without) Machine Learning experience. Chapter II presents the process of gathering and preparing the dataset, while the next chapter presents the creation of a Machine Learning model, model training using the acquired dataset, and the model performance. It was possible to obtain the result of 92.4% validation accuracy for the squat movement pattern classification model. The trained model can be used in an ML smartphone application for evaluation of user-provided examples of squats.

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control System of an Autonomous Object Tracking Robot 17

Control System of an Autonomous Object Tracking Robot

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17th International Conference on engineering of Modern Electric Systems, EMES 2023

作者： Barabas, Tiberiu Silaghi, Helga Spoiala, Dragos Gamcova, Maria University of Oradea Control Systems Engineering and Management Department Oradea Romania Technical University of Kosice Faculty of Electrical Engineering and Informatics Kosice Slovakia

ISBN: (纸本)9798350310634

This paper presents the control system of a mobile robot, capable of detecting, tracking and following an object of a certain color. The mobile robot was created for educational purposes, in the CIM laboratory of the University of Oradea. It is based on a crawler robot, controlled with a Raspberry Pi development system. This system controls the movements necessary for tracking the object: moving forward, backward, left turn or right turn. For detecting and locating the object, the robot is also equipped with a video camera connected to Raspberry Pi. The acquisition and processing of images in real time, provided by the camera, are performed with programming functions provided by the OpenCV (Open Source Computer Vision Library). These functions are implemented in a control program, written in Python language. In order to facilitate the tracking of the images obtained and processed during the movements, the robot has also been provided with a graphic display connected to the Raspberry Pi board. This paper also presents the implementation of a numerical control algorithm used for tracking the objects. © 2023 IEEE.

关键词： Python

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Analysis of selected dielectric parameters of insulating liquids

Analysis of selected dielectric parameters of insulating liq...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Aleksandra Płużek Łukasz Nagi Michał Kozioł Małgorzata Zygarlicka Department of Electrical Power and Renewable Energy Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength.

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Life Cycle Management in Oil&Gas Products Industry 17

Life Cycle Management in Oil&Gas Products Industry

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17th International Conference on engineering of Modern Electric Systems, EMES 2023

作者： Magdoiu, Liliana Doina Caciora, Simona Veronica Abrudan Pacala, Anca Gamcova, Maria University of Oradea Control Systems Engineering and Management Department Oradea Romania Technical University of Kosice Faculty of Electrical Engineering and Informatics Kosice Slovakia

ISBN: (纸本)9798350310634

The life cycle of a petroleum product reflects the evolution of its sales volume over time and represents the interval between its introduction on the market and its definitive disappearance from the commodity exchange arena. During the life cycle of a petroleum product, the company marketing it will keep on reformulating the adopted marketing strategies, as determined by variable conditions and new challenges on the side of the competition, along with the changes in customers' interests and their requirements in relation to the product;therefore, appropriate marketing strategies must be developed for each stage in the life cycle of the petroleum product in order to increase its marketing profitability, even though its existence is limited over time. © 2023 IEEE.

关键词： Life cycle

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A New Task-Space Neural Nonlinear control Approach for Robotic Manipulators under Joint Constraints

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IEEE Access 2025年 13卷 91945-91956页

作者： Nguyet, Nguyen Tran Minh Ba, Dang Xuan Faculty of Electrical and Electronics Engineering Department of Automatic Control Ho Chi Minh City71307 Viet Nam

Robotic manipulators are nonlinear systems with multi-input multi-output (MIMO) structures, uncertainties, and time-varying dynamical prospects. Unexpected influences of internal and external disturbances along with physical constraints in complicated kinematic configurations are large barriers for deriving excellent controllers of the manipulators. In this paper, we propose a novel two-level control approach to drive the end-effector of robotic manipulators following referenced profiles within the hard bounds of joint angles without using inverse kinematics solutions. A new Cartersian-based high-level sub controller is designed for calculating the desired angular velocities from the task-space control objective throughout a constrained-to-free transformation operator. An advanced sliding mode control framework is adopted to construct the low-level control layer to realize the indirect joint-control missions given from the upper one within the physical bounds. To effectively suppress the dynamical internal and external disturbances, a new neural network with a flexible nonlinear learning law is integrated in the joint-space sub controller. Stability of the whole system including both Cartersian and joint spaces is thoroughly proven by a Lyapunov function under a special constraint. The designed controller was verified on a two-link planar robotic arm in various challenging conditions and in comparing with other state-of-the-art control methods. The in-depth simulation results exhibited that the proposed control algorithm possesses outperformance working abilities such as model-free adaptation, robustness, high accuracy and comprehensiveness. © 2013 IEEE.

关键词： Robotic arms

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Deep Reinforcement Learning Method for control of Mixed Autonomy Traffic Systems

Deep Reinforcement Learning Method for Control of Mixed Auto...

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2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2024

作者： Liu, Xingyu Apriaskar, Esa Mihaylova, Lyudmila University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Universitas Negeri Semarang Faculty of Engineering Department of Electrical Engineering Semarang50229 Indonesia

ISBN: (纸本)9798350368031

The introduction of autonomous vehicles (AVs) presents a novel approach to regulating and optimising traffic flow through the automated control of AVs. In this context, the AV is defined as the actuator and an optimal control policy is desired to make control decisions. Deep Reinforcement Learning (DRL) is a novel method which aims to maximize the cumulative rewards given by the predefined reward function by making sequential decisions in a stochastic environment. In light of the above, we propose a DRL-based vehicular control method to train an optimal policy for the control of AV in a model-free fashion, and consequently improve the traffic efficiency with the obtained control policy. A single-lane circular road environment with both AV and human-driven vehicles is selected to serve as the mixed autonomy traffic system in the Simulation of Urban MObility (SUMO) [1] traffic simulator, and the Proximal Policy Optimization (PPO) algorithm is applied for the policy improvement. Simulation results demonstrate that our strategy is effective in mitigating the unstable stop-and-go waves, increasing 67.7% of the average driving speed and reducing 19.3% of the average energy consumption in a closed-ring road environment. © 2024 IEEE.

关键词： Deep reinforcement learning

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Split Cost Function based Single-Horizon Finite-Set Model Predictive control for Boost Converter with Loading Current Estimation

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Tatari, Fatemeh Rezayof Bizhani, Hamed Iwanski, Grzegorz Warsaw University of Technology Faculty of Electrical Engineering Warsaw Poland Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Kielce Poland

This paper presents a robust single-horizon finite-set model predictive control (FS-MPC) method for controlling the output voltage of boost converters. Unlike the long-horizon FS-MPC approach, which addresses the non-minimum phase (NMP) behavior of the converter by extending the prediction horizon (thereby increasing computational effort), the proposed method ensures stable voltage regulation by incorporating inductor current regulation into the cost function. To achieve this, the desired inductor current is calculated based on input-output power balance theory. Unlike recent studies that require an additional sensor to measure the loading current, this paper develops a loading current estimation approach to eliminate the need for extra current sensors, thereby enhancing the robustness of the proposed FS-MPC method. Additionally, over-current protection, which is typically absent in conventional FS-MPC used for direct voltage regulation, is also incorporated into the proposed method. The conventional cost function is also modified to tackle the NMP behavior more effectively. The performance of the proposed method in regulating the output voltage is evaluated through simulation results. Finally, its effectiveness across a wide range of output power and various load characteristics, including resistive, constant power, and constant current loads, is validated via experimental results. The results demonstrate that the proposed method is not only able to eliminate the overshoot and undershoot, but can also improve the settling time by 41% compared to a well-tuned conventional cascaded PI controller. In addition, the proposed method can reduce the computational burden by 84% compared to the conventional long-horizon FS-MPC approach. © 2013 IEEE.

关键词： Cost functions

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The concept of an expert system for partial discharge assessment in power transformers 6

The concept of an expert system for partial discharge assess...

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6th International Conference on Nanotechnology for Instrumentation and Measurement, NanofIM 2021

作者： Kunicki, Michal Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole Poland

ISBN: (纸本)9781665407007

This paper describes the idea of novel approach to creating an expert system for partial discharge (PD) assessment in power transformers. The proposed system is intended to support the decision-making process regarding technical condition assessment of power transformers. The primal objective of this study is to share the idea with the academia and industry in order to find potential partners interested in practical realization of such a solution. Moreover, this paper analyzes state of the art in the field of expert systems for PD, introduces experience and competences of the research team involved in this project, and presents the results of surveys among industrial entities representing the point of view and needs of the transformer market in this matter. Results show that in most cases, contemporary PD analysis systems do not meet all the needs of their end users, and proposed expert system is sought by the industry, and would be willingly used in their practice. © 2021 IEEE.

关键词： Partial discharges

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