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American control Conference (ACC)

作者： Hebertt J. Sira-Ramírez Brian C. Gómez-León Mario A. Aguilar-Orduña Electrical Engineering Department Center for Research and Advanced Studies (Cinvestav-IPN) Mexico City Mexico Automatic Control Department Center for Research and Advanced Studies (Cinvestav-IPN) Mexico City Mexico

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

In this article, we present a general approach to control switched Hamiltonian systems via a sliding motion defined on a manifold of the system's phase space. The geometric features of classical Hamiltonian systems are exploited in the formal definition of sliding regimes taking place in the phase space of the system and the establishment of necessary and sufficient conditions for the existence of a local sliding regime on a pre-specified manifold which generates a desired closed loop dynamics. An example is presented which illustrates the approach.

关键词： Manifolds Sufficient conditions Switches Aerospace electronics Sliding mode control

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Weighted Fuzzy Rough Sets Feature Selection for High Dimensional Classification Problems

Weighted Fuzzy Rough Sets Feature Selection for High Dimensi...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Simon Peter Khabusi Yo-Ping Huang Van Phong Vu Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Electrical Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Automatic Control Ho Chi Minh City University of Technology and Education Ho Chi Minh City Vietnam

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Feature selection holds significant importance in knowledge mining as it plays a pivotal role in selecting and preserving the most informative features within a dataset while discarding irrelevant, redundant, or noisy attributes. This process contributes to enhancing model performance, reducing computational complexity, and refining interpretability, thus facilitating more accurate and efficient data analysis. In high-dimensional datasets, the necessity for feature selection becomes more pronounced due to the heightened risk of encountering the curse of dimensionality. Therefore, this study proposes a weighted fuzzy rough quickreduct (FRQR) feature selection approach employing feature weights to handle the equal situation problem inherent in FRQR. The proposed method is evaluated on ten publicly available datasets with feature sizes ranging from 2000 to 15154. The selected features are used to train and test random forest candidate models whose estimates are then combined according to the posterior probabilities by Bayesian Model Averaging (BMA). The performance of the model on the selected features is evaluated on four performance metrics. The essentiality of the selected features is further determined by comparing the model classification performance achieved on the non-selected features and all the dataset features. The results indicate competitiveness in the performance metric values achieved on selected features over the other two feature categories affirming the efficacy of the proposed method.

关键词： Data analysis Posterior probability Refining Rough sets Feature extraction Distance measurement Data models Noise measurement Data mining Diseases

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DAFNI: A computational platform to support infrastructure systems research

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Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction 2023年第3期176卷 108-116页

作者： Matthews, Brian Hall, Jim Batty, Michael Blainey, Simon Cassidy, Nigel Choudhary, Ruchi Coca, Daniel Hallett, Stephen Harou, Julien J James, Phil Lomax, Nik Oliver, Peter Sivakumar, Aruna Tryfonas, Theodoros Varga, Liz Scientific Computing Department Science and Technology Facilities Council Didcot United Kingdom School of Geography and the Environment University of Oxford Oxford United Kingdom Centre for Advanced Spatial Analysis University College London London United Kingdom Transportation Research Group Faculty of Engineering and Physical Sciences University of Southampton Southampton United Kingdom Department of Civil Engineering University of Birmingham Birmingham United Kingdom Department of Engineering University of Cambridge Cambridge United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Centre for Environmental and Agricultural Informatics Cranfield University Cranfield United Kingdom Department of Mechanical Aerospace and Civil Engineering University of Manchester Manchester United Kingdom School of Engineering Newcastle University Newcastle United Kingdom School of Geography University of Leeds Leeds United Kingdom Department of Civil and Environmental Engineering Imperial College London London United Kingdom Department of Civil Engineering University of Bristol Bristol United Kingdom Department of Civil Environmental and Geomatic Engineering University College London London United Kingdom

Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project. © 2023 Emerald Publishing Limited: All rights reserved.

关键词： Urban growth

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Event-Triggered ℋ∞ Optimal control for Euler-Lagrange Dynamics with Dead Zone Inputs under Attacks on Sensors and Actuators

Event-Triggered ℋ∞ Optimal Control for Euler-Lagrange Dyna...

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International Symposium on electrical and Electronics engineering (ISEE)

作者： Luy Nguyen Tan Dung Nguyen Le Quoc Phan Nguyen Phuc Lam Phan Huynh Thanh Pham Cong Department of Automatic Control Faculty of Electrical-Electronics Engineering (FEEE) VNUHCM-Ho Chi Minh City University of Technology Vietnam Faculty of Electrical-Electronics Engineering Vietnam Aviation Academy Vietnam

Optimal control has been investigated for Euler-Lagrange (EL) systems. However, the existing methods have not yet considered the input constraints due to dead zones and vulnerabilities caused by malicious attackers. In this paper, we propose a novel control algorithm to gain the bounded ℒ 2 -gain tracking performance with deadzone disturbance rejection and to reduce not only the effects of sensor and actuator attacks but also the burden of communication load. Firstly, an event-triggered (ET) observer is studied to conjecture the unmeasurable states and compensate for the adverse attack effects. Secondly, ET augmented control is proposed to transform Euler-Lagrange dynamics into tracking error dynamics. Thirdly, an ET ${{\mathcal{H}}_\infty }$ optimal control law is approximated via adaptive dynamic programming (ADP). Finally, the simulation of mobile nonholonomic robots illustrates the effectiveness of the proposed method.

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Mobile Application for Visualizing the Measurements 5

Mobile Application for Visualizing the Measurements

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5th IEEE International Conference on Modern electrical and Energy System, MEES 2023

作者： Kiresova, Simona Guzan, Milan Sobota, Branislav Melnykov, Viacheslav Yatsiuk, Rostyslav Peryvertailo, Bohdan Technical University of Košice Dept. of Theoretical and Industrial Electrical Engineering Košice Slovakia Technical University of Košice Dept. of Computers and Informatics Košice Slovakia Kremenchuk Mykhailo Ostrohradskyi National University Dept. of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine National University Dept. of Computer Engineering and Electronics Kremenchuk Mykhailo Ostrohradskyi Kremenchuk Ukraine

ISBN: (纸本)9798350359787

This paper deals with the design of an Android mobile application and visualization of the measured values of particulate matter and meteorological factors from the measurement stations. The application can in principle be effectively used in any field of data visualization. The architecture of the mobile application, the security, the use of AWS services to access the data in the InfluxDB databases, as well as the user interface and graphical visualizations of the measured data are described and illustrated. The application is user tested and the paper documents their first experiences using the mobile application. © 2023 IEEE.

关键词： Visualization

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Analysis of YouTube Video Comments with NLP Methods

Analysis of YouTube Video Comments with NLP Methods

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pirnau Mironela Priescu Iustin Priescu Catalina Mihaela Pirnau Claudiu Ghiculescu Liviu Daniel Department of Informatics Faculty of Informatics “Titu Maiorescu” University Bucharest Romania Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania Manufacturing Engineering Department Faculty of Industrial Engineering and Robotics National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of “ChatGPT, AI clone, AI robot and Deep Learning.”

关键词： Video on demand Social networking (online) Education Tutorials Chatbots Web sites Artificial intelligence

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Attack Stealthiness and Detection of Multiagent Systems: A Zero-Sum Formulation

Attack Stealthiness and Detection of Multiagent Systems: A Z...

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IEEE Conference on Decision and control

作者： Shiyong Zhu Miaomiao Wang Jie Chen Anders Rantzer Department of Electrical Engineering City University of Hong Kong Hong Kong China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Department of Automatic Control Lund University Lund Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Cybersecurity has in recent years emerged as a paramount concern in the design and operation of industrial systems and civil infrastructures, due mainly to their susceptibility to malicious cyber attacks which take advantage of the vulnerability of communication networks and IT devices. In this paper, we investigate such an attack and counter attack scenario by considering multiagent systems, a somewhat basic prototype of cyberphysical systems. We study false data injection attacks launched on the agent sensors, and possible defense of such attacks at the agent actuators. The primary issue under consideration is the stealthiness of the attacks, while steering a multiagent system away from its consensual state. We propose a metric to quantify the stealthiness, and formulate the stealthiness problem as one of zero-sum games. We solve the problem explicitly, which gives rise to a fundamental bound on the stealthiness achievable, and as well optimal attack and defense strategies that achieve the optimal stealthiness, both of which can be obtained in terms of certain augmented controllability Gramians associated with the agents. The stealthiness bound is seen to depend on agent dynamics and network characteristics including a measure of connectivity.

关键词： Actuators Protocols Prototypes Games Sensor phenomena and characterization controllability Sensor systems Game theory Observability Multi-agent systems

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control System of an Autonomous Object Tracking Robot

Control System of an Autonomous Object Tracking Robot

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International Conference on engineering of Modern Electric Systems (EMES)

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

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.

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DATASISMO: A model for the forecast of health needs via analysis of the demand for supplies and medicines 6

DATASISMO: A model for the forecast of health needs via anal...

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6th Congreso Internacional en Inteligencia Ambiental, Ingenieria de Software y Salud Electronica y Movil, AmITIC 2023 - 6th International Congress on Environmental Intelligence, Software engineering and Electronic and Mobile Health, AmITIC 2023

作者： Chang, Ignacio Alvarez, Humberto R. Aguilar, Orlando Garcia, Antony Cabrera, Victor L. Castillo, Juan Marcos Univversidad Tecnologica de Panama Department of Control and Instrumentation Engineering Panama Panama Univversidad Tecnologica de Panama Industrial. Engineering Department Panama Panama Univversidad Tecnologica de Panama Mechanical Engineering Department Panama Panama Ingenieria Electrica Univversidad Tecnologica de Panama Electrical Engineering Department Panama Panama Ingenieria Electrica Univversidad Tecnologica de Panama Departament of Information Control Systems and Evaluation of Informatics Resources Panama Panama Ingenieria Electrica Univversidad Tecnologica de Panama CIDITIC/CIDETYS AIP Panama Panama

ISBN: (纸本)9798350318692

At the end of 2019, the disease later known as COVID-19 emerged, causing the recent pandemic. The objective of this study was to propose an adaptive mathematical model with the capacity to forecast the health needs of the conntry in the face of the pandemic situation, based on the health needs and the demands for supplies, medicines and other resources identified in the database of the Ministry of Health from the Republic of Panama. In addition, information from the GitHub Repository of the John Hopkins University Center for Systems Science and engineering was considered. A quantitative methodology was used from existing data, based on a mixed approach that incorporated dynamic simulation, machine learning and Six-Sigma design. A monitoring model has been developed focused on reducing health risk due to shortages of medicines and medical supplies in the event of a pandemic or similar situation. This research has laid the foundations for the development of epidemiological models in Panama to facilitate data processing, providing a complementary tool for decision-making based on short-Term predictions, which is expected to achieve a better distribution of health resources in the country in cases of national health emergency. © 2023 IEEE.

关键词： Supply chains

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Small Signal Stability Analysis of Multi-Machine Power System Using Genetic Algorithm Technique

Small Signal Stability Analysis of Multi-Machine Power Syste...

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International Conference on Systems and control (ICSC)

作者： Moncef Triki Bilel Dhouib Soufien Hajji Hsan Hadj Abdallah Electrical Engineering Department Sfax Engineering School Control & Energy Management Laboratory Sfax Engineering School Sfax Tunisia Electrical Engineering Department Sfax Laboratory of Sciences and Techniques of Automatic & computer engineering (Lab-STA) Sfax Engineering School Sfax Tunisia

This paper introduces an innovative approach for determining the dynamic stability margin of a power system. The method employs a Genetic Algorithm (GA) to optimize the parameters of a Conventional Power System Stabilizer (CPSS) linked with the automatic Voltage Regulator (AVR) in a multi-machine power system. The objective is to tune the stabilizers in a way that effectively shifts the lightly damped and undamped electromechanical modes of all plants to a specified region in the s-plane. To achieve this, a multiobjective problem is formulated, optimizing a composite set of objective functions that include the damping factor of the lightly damped electromechanical modes. The dynamic behavior of the system is assessed using small signal stability analysis, while the stability of the system is evaluated by monitoring the variations of eigenvalues under line-to-ground (LG) fault conditions. The proposed method is then demonstrated on a 3-machine 9-bus system, and the effectiveness and robustness of the suggested Power System Stabilizers (PSSs) are showcased by incorporating them into a conventional AVR-PSS model. This allows the proposed approach to efficiently damp low-frequency oscillations in the power system.

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