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Energy Internet:Redefinition and categories

Energy Internet 2024年第1期1卷 3-8页

作者： Hongbin Sun Qinglai Guo Xinwei Shen Yixun Xue Mohammad Shahidehpour Nikos Hatziargyriou Department of Electrical Engineering Tsinghua UniversityBeijingChina College of Electrical and Power Engineering and Key Laboratory of Cleaner Intelligent Control on Coal&Electricity Ministry of EducationTaiyuan University of TechnologyTaiyuanChina Shenzhen International Graduate School Tsinghua UniversityShenzhenChina Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIllinoisUSA National Technical University of Athens AthensGreece

The concept of‘Energy Internet’(EI)has been widely accepted by both academic and industry experts after more than a decade of *** it was proposed,EI has been discussed and applied to many technical works in power and energy *** specific definitions were proposed for EI by those who have applied it to respective fields of engineering,but a comprehensive and widely accepted definition of EI is still being *** this paper,we propose the redefinition of EI,based on a comprehensive literature review,some latest trends and driving forces in the global energy industry,as well as its development in the past *** addition,we summarise the EI framework and features for future applications,where EI is categorised by its scale into local‐and wide‐area applications to manifest its effectiveness in power and energy.

关键词： categories Energy Internet redefinition

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无人飞行器在不确定扰动下的动态目标跟踪

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engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle Visual servoing Velocity observer Target tracking

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Dissipative Avoidance Feedback for Reactive Navigation Under Second-Order Dynamics

arXiv

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arXiv 2024年

作者： Smaili, Lyes Tang, Zhiqi Berkane, Soulaimane Hamel, Tarek Department of Computer Science and Engineering University of Quebec in Outaouais GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden Department of Electrical Engineering Lakehead University ON Canada France

This paper introduces DAF (Dissipative Avoidance Feedback), a novel approach for autonomous robot navigation in unknown, obstacle-filled environments with second-order dynamics. Unlike traditional APF (Artificial Potential Field) methods, which rely on repulsive forces based solely on position, DAF employs a dissipative feedback mechanism that adjusts the robot’s motion in response to both its position and velocity, ensuring smoother, more natural obstacle avoidance. The proposed continuously differentiable controller solves the motion-to-goal problem while guaranteeing collision-free navigation by considering the robot’s state and local obstacle distance information. We show that the controller guarantees safe navigation in generic n-dimensional environments and that all undesired ω-limit points are unstable under certain controlled curvature conditions. Designed for real-time implementation, DAF requires only locally measured data from limited-range sensors (e.g., LiDAR, depth cameras), making it particularly effective for robots navigating unknown workspaces. © 2024, CC BY.

关键词： Feedback

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Cardiac Ischemia Detection Using Self-Organizing Map Feature Selection Method

Cardiac Ischemia Detection Using Self-Organizing Map Feature...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Ramin Aghili Karampour Amir Arshia Bakhtiar Kiarash Hajizamani Alireza Fallahi Hamid Soltanian Zadeh Biomedical Engineering Department Hamedan University of Technology Hamedan Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (数字)9798331529710

ISBN: (纸本)9798331529727

Cardiac ischemia, a prevalent cause of heart failure, remains the leading cause of death in Iran. Early diagnosis of this condition is crucial, and electrocardiogram (ECG) signal processing techniques offer valuable insights. By analyzing ECG signals from ischemic patients and comparing them to those of normal individuals, we can extract relevant features for classification. Our study extracted some features from ECG signals, including statistical, time-based, frequency, and time-frequency features. We employed the self-organizing maps method (SOM) to identify the most informative features. Subsequently, we evaluated the classification accuracy using several machine learning algorithms, including support vector machines (SVM), Naive Bayes, Linear Discriminant Analysis (LDA), and Logistic Regression. The results demonstrated the superiority of the SOM method in selecting the best features compared to PCA, with accuracies of $\mathbf{9 1. 2 \%}, \mathbf{8 4. 3 \%}, \mathbf{7 2. 5 \%}$, and $88.9 \%$ for SVM, LDA, NB, and LR methods, respectively. Our findings contribute to the early detection and management of cardiac ischemia, potentially improving patient outcomes.

关键词： Self-organizing feature maps Support vector machines Time-frequency analysis Logistic regression Accuracy Machine learning algorithms Electrocardiography Signal processing Feature extraction Principal component analysis

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Two-Player Incomplete Games of Resilient Multiagent Systems

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IFAC-PapersOnLine 2023年第2期56卷 258-263页

作者： Yurid E. Nugraha Tomohisa Hayakawa Hideaki Ishii Ahmet Cetinkaya Quanyan Zhu Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama 226-8502 Japan Department of Functional Control Systems Shibaura Institute of Technology Tokyo 135-8548 Japan Department of Electrical and Computer Engineering New York University Brooklyn NY 11201 USA

Evolution of agents’ dynamics of multiagent systems under consensus protocol in the face of jamming attacks is discussed, where centralized parties are able to influence the control signals of the agents. In this paper we focus on a game-theoretical approach of multiagent systems where the players have incomplete information on their opponents’ strength. We consider repeated games with both simultaneous and sequential player actions where players update their beliefs of each other over time. The effect of the players’ optimal strategies according to Bayesian Nash Equilibrium and Perfect Bayesian Equilibrium on agents’ consensus is examined. It is shown that an attacker with incomplete knowledge may fail to prevent consensus despite having sufficient resources to do so.

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Abstracting Linear Stochastic Systems via Knowledge Filtering

arXiv

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arXiv 2023年

作者： Engelaar, Maico Hendrikus Wilhelmus Romao, Licio Gao, Yulong Lazar, Mircea Abate, Alessandro Haesaert, Sofie Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Netherlands Department of Computer Science University of Oxford United Kingdom

In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques. This new technique will reduce the dimension of the noise disturbance and will allow any controller designed for the reduced model to be refined into a controller for the original stochastic system, while preserving any specification on the output. Although initially the reduced model will be time-varying, a method will be provided with which the reduced model can become time-invariant if it satisfies some minor technical conditions. We present our theoretical findings with an example that supports the proposed framework and illustrates how model reduction and controller refinement of stochastic systems can be achieved. We finish the paper by considering specific examples to analyze both completeness with respect to controller synthesis and model order reduction with respect to the state. © 2023, CC BY-NC-ND.

关键词： Stochastic systems

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Social and Ethical Issues in Various Medical Procedures

Social and Ethical Issues in Various Medical Procedures

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Progress in Applied electrical engineering (PAEE)

作者： Piotr Sterniuk Waldemar Karwowski Henryk Racheniuk Adrian Luckiewicz Anna Wieczorek Mateusz Paw၂owski Witold Libionka Anna W၂odarczyk Katarzyna Bojkowska-Otrebska Adam Sudo၂ Bartosz Pańczyszak Aleksandra Kawala-Sterniuk Technology Transfer Center Opole University of Technology Opole Poland Department of Industrial Engineering and Management Systems University of Central Florida Orlando FL USA Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Vital Medic Hospital Kluczbork Poland Faculty of Health Sciences Wroclaw Medical University Wroclaw Poland Department of Neurosurgery Medical University of Gdansk Gdansk Poland Faculty of Stobrawskie Centrum Medyczne Clinical Department of Geriatrics Kup Poland Institute of Medical Sciences University of Opole Opole Poland Faculty of Natural Sciences and Technology University of Opole Opole Poland Faculty of Health Sciences Jan Dlugosz University in Czestochowa Czestochowa Poland

Medical procedures, in particular those invasive, generate significant ethical, legal, and social concerns, including the issues of humanity and person-hood, stigma, autonomy, privacy and security, research ethics, safety, moral and legal responsibility, fair access, and justice. It was pointed out that future research should focus on developing practical solutions to the ethical challenges of medical experimental procedures with human participants, facilitated by the collection of empirical data on the perspectives shared by the general public, researchers and of course study participants.

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Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

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IEEE International Conference on Big Data

作者： Krzysztof Hanzel Damian Grzechca Adam Ziebinski Lukas Chruszczyk Artur Janus Department of Telecommunications and Teleinformatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Distributed Systems and Informatics Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Student of Electrical Engineering Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested; however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV – so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime.

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Abstracting Linear Stochastic Systems via Knowledge Filtering

Abstracting Linear Stochastic Systems via Knowledge Filterin...

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IEEE Conference on Decision and control

作者： M.H.W. Engelaar L. Romao Y. Gao M. Lazar A. Abate S. Haesaert Department of Electrical Engineering (Control Systems Group) Eindhoven University of Technology The Netherlands Department of Computer Science University of Oxford United Kingdom

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Enhancing Fault Detection in Induction Motors using LSTM-Attention Neural Networks

Enhancing Fault Detection in Induction Motors using LSTM-Att...

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International Conference on control, Instrumentation, and Automation

作者： Mohammad Ali Labbaf Khaniki Marzieh Mirzaeibonehkhater Mohammad Manthouri Department of Control Engineering K.N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Indiana University-Purdue University Department of Electrical and Electronic Engineering Shahed University Tehran Iran

Induction motors carry notable importance in modern machinery and industrial equipment. Hence, the imperative to establish an early fault detection system for discerning operational states and potential faults in these motors is evident. This paper introduces a pioneering methodology for fault detection in induction motors by leveraging the power of Long Short-Term Memory (LSTM) networks and attention mechanisms within a neural network framework. By combining the temporal sequence analysis capabilities of LSTMs with the selective focus feature of attention mechanisms, the proposed architecture enhances the accuracy and timeliness of fault detection, paving the way for improved machinery health monitoring and predictive maintenance. The proposed approach is rigorously evaluated alongside established methods, including simple Artificial Neural Networks (ANN) and LSTM networks to showcase the strengths of the LSTM-Attention approach. This comprehensive analysis reveals the additional advantages of attention mechanisms and positions the LSTM-Attention architecture as a robust solution for detecting faults in induction motors.

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