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63rd IEEE Conference on Decision and control, CDC 2024

作者： Breukelman, Enno Sandberg, Henrik Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Division of Decision and Control Systems Malvinas väg 10 StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

Driven by ubiquitous digitalization and cyberattacks on critical infrastructure, there is a high interest in research on the security of cyber-physical systems. If an attacker gains access to protected and sensitive information, such as the internal states of a control system, this is considered a breach of confidentiality. Access to sensitive information can be the first step in a larger cyber-attack scheme, such as a stealthy false data injection attack. Considering process and measurement noise in the plant, existing research investigated when an attacker equipped with a Kalman filter can perfectly estimate the internal controller states if the attacker has access to plant measurements and all model parameters. For this estimate to converge, the controller is required to have stable poles. In this paper, we show that if the attacker has access to the control inputs instead of the plant measurements, the controller needs to have stable zeros. Additionally, we demonstrate that an attacker equipped with an Unknown Input Observer, using tools from delayed system inversion, can get a delayed yet perfect estimate of the controller states from the control inputs without knowledge of the plant's parameters and noise characteristics. Lastly, we present simulation results from a three-tank system to showcase the differences in controller state estimation. © 2024 IEEE.

关键词： Delay control systems

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Comparison of Two AC Current De-tumbling Methods for Uncooperative Space Target through Electromagnetic Characteristic Analysis 1

Comparison of Two AC Current De-tumbling Methods for Uncoope...

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1st Aerospace Frontiers Conference, AFC 2024

作者： Du, Lei Chen, Zhen Hu, Hengzai Liu, Xiangdong Zhang, Qiang Zhang, Kemo Liu, Hui School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100191 China Beijing Institute Computer for Application Beijing100089 China

ISBN: (纸本)9781510681613

A large number of space debris with rotational motion occupy scarce orbital resources, thus, a de-tumbling phase may be necessary prior to the capturing phase to reduce the risk of collision. A new contactless AC current de-tumbling method based on the principle of electromagnetic eddy current is proposed in this paper. Firstly, an analysis is conducted on external disturbances affecting the attitude of the debris and de-tumbling device, such as magnetic field perturbations. Compared to the electromagnetic forces acting on de-tumbling device, the influence of the geomagnetic force on detumbling device can be negligible. However, the geomagnetic torque acting on de-tumbling device cannot be ignored. Then, the advantages and disadvantages of the two AC current cases are compared and analyzed, and the method to increase the de-tumbling torque can be obtained by adjusting the frequency of the three phase AC current. Finally, the three-dimensional attitude dynamics of the uncooperative space target is established taking a spinning cylinder as the hypothetical target of de-tumbling. Simulation shows that the de-tumbling method is effective and the de-tumbling rate can be greatly improved by adjusting the frequency of the three phase AC current. © 2024 SPIE.

关键词： Space debris

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Where to Turn: Road Fork Detection in Sparse 3D Point Cloud 3rd

Where to Turn: Road Fork Detection in Sparse 3D Point Clou...

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Hu, Di Zhang, Kai Zhong, Yipan Xu, Jiachen Yuan, Xia Zhao, Chunxia School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Research Institute of Intelligence Southwest Research Institute of Information Control Chengdu611700 China

ISBN: (纸本)9789819711024

Intersection detection plays a crucial role in localizing and planning the path of autonomous vehicles in urban environments. This paper presents a novel approach, PVWO, for adaptive intersection detection in autonomous vehicles equipped with 3D LiDAR. Firstly, the algorithm removes ground and obstacles effectively, and eliminates noise points. Secondly, a polyarticular viewpoints beam model is applied to detect the type and location of intersections. Thirdly, a linear feature extraction approach in a rolling window is proposed to detect road width and optimize key parameters, enhancing model robustness across different scenes. Compared to parallel intersection detection algorithms, our method exhibits excellent performance under diverse road conditions. Experiments in sparse point clouds show an average precision exceeding 89% and an average processing time of approximately 88 ms/frame. These results demonstrate that our method can accurately detect intersections in real-time, across various road structures. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Extraction

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Autonomous Surveillance Breakthrough by Implementing Facial Recognition in Dog Robots

Autonomous Surveillance Breakthrough by Implementing Facial ...

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2024 Intermountain engineering, Technology and Computing, IETC 2024

作者： Hafezi, Amir Zibran, Minhaz Deemyad, Taher Idaho State University Department of Mechanical and Measurement & Control Engineering PocatelloID United States Idaho State University Department of Computer Science PocatelloID United States

ISBN: (纸本)9798350373073

As the importance of security in today's world continues to escalate, technology's role in its enhancement has evolved significantly. From the inception of fixed security cameras monitored by individuals, advancements have steered towards autonomous threat recognition systems and the deployment of mobile robots for proactive security measures. Despite these technological strides, the exploration of autonomous robots in security has been relatively scant. This study takes a novel approach by repurposing the commercial GO2 Edu dog robot for security purposes, equipping it with a thermal camera and custom software for robust face detection in varying lighting conditions, aimed at achieving safer and more reliable face recognition. Furthermore, the mapping and navigational capabilities are studied by conducting experiments with a Turtlebot outfitted with a 2D RPLIDAR and depth camera using SLAM, laying the groundwork for the GO2 robot's autonomous operations. The results of these enhancements have shown to be promising in the context of bolstering security measures. The paper concludes with a discussion on potential future enhancements, paving the way for more sophisticated and autonomous security robots. © 2024 IEEE.

关键词： Face recognition

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Fractional-order binary bat algorithm for feature selection on high-dimensional microarray data

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7453-7467页

作者： Esfandiari, Ahmad Farivar, Faezeh Khaloozadeh, Hamid Department of Computer and Mechatronics Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Systems and Control Faculty of Electrical Engineering K. N. Toosi University of Technology Seyed-Khandan Shariati Ave. Tehran16317-14191 Iran

High-dimensional microarray data suffer from the confounding effects of irrelevant, redundant and noisy genes on the scalability and efficiency of classification algorithms. In order for an effective dimensionality reduction and the selection of informative genes, this paper introduces a novel approach using fractional calculus concepts. This study proposes a modified version of binary the bat algorithm named fractional-order binary bat algorithm (FBBA) able to control the convergence process using more historical memory of bat behaviors. The gene selection technique contains a two-stage hybrid filter/wrapper method which employs a new correlation-based feature clustering (CFC) algorithm in the filter stage and the FBBA in the wrapper stage. The CFC-FBBA is evaluated on ten microarray gene expression datasets by employing the support vector machine classifier with a k-fold Monte Carlo cross validation data partitioning model. Furthermore, the results show that the CFC-FBBA, while minimizing the size of the gene subset, achieves the highest classification accuracy in most cases compared to several state-of-art hybrid techniques. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Classification (of information)

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Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1026-1036页

作者： Jingyang Mao Xiangyu Meng Derui Ding Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Division of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA70803 USA IEEE School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership ***,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy ***,compared to traditional prediction-based ones,two types of fuzzy set-membership filters are proposed to effectively improve filtering performance,where the structure of both filters consists of two parts:prediction and *** the locally Lipschitz continuous condition of membership functions,unknown membership values in the estimation error system can be treated as multiplicative noises with respect to the estimation ***-time recursive algorithms are given to find the minimal ellipsoid containing the true ***,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.

关键词： Affine model membership functions set-membership filtering stability Takagi-Sugeno fuzzy modeling

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Development and Analysis of Genetic Algorithm for Optimization of Continuous Cast Billets Warehousing Process

Development and Analysis of Genetic Algorithm for Optimizati...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Shchegolikhin, Ivan S. Andreev, Sergey M. Nosov Magnitogorsk State Technical University Department of Computer Engineering and Programming Magnitogorsk Russia Nosov Magnitogorsk State Technical University Department of Automated Control Systems Magnitogorsk Russia

ISBN: (纸本)9798350395044

Warehouses are an important logistic component of various companies. Warehouses may have different layouts, equipment and their own features. Optimization of warehouse operations can decrease overhead costs and increase the economic efficiency of industry. The technological process of steel sheet production at a metallurgical company includes two major stages: casting of liquid steel into billets and rolling of these billets on a rolling mill. In order to coordinate the productivity of these two stages and to be able to fulfill orders promptly, a warehouse of slabs (billets) is used. Billets of different parties and steel grades are stored in stacks. The billets are moved to the warehouse for storage and from the warehouse to the rolling mill by bridge cranes. In this paper the problem of optimization of the process of continuous cast billets storage is solved to minimize the number of slab handling operations. The problem is decomposed into two subproblems SLAP (Storage Location Assignment Problem) and CSP (Crane Scheduling Problem). A modified genetic algorithm was applied to solve the problem. Using a simulation model of the warehouse, the efficiency of the algorithm was evaluated using different approaches to take the restrictions imposed on the process of slab handling into account. It is shown that the most effective is the algorithm in which there is no restriction on the placement of stacks of billets belonging to one melting. © 2024 IEEE.

关键词： Genetic algorithms

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Spectral graph theory to investigate topological and dynamic properties of EEG-based brain networks: An application to post-stroke patients 46

Spectral graph theory to investigate topological and dynamic...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Ranieri, Andrea Pichiorri, Floriana Mongiardini, Elena Colamarino, Emma Cincotti, Febo Mattia, Donatella Toppi, Jlenia Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Fondazione Santa Lucia Hospital Neuroelectrical Imaging and Bci Laboratory Rome00179 Italy

ISBN: (纸本)9798350371499

Brain networks represent one of the most fascinating biophysics contributions to modern medicine. Nowadays clinical practice largely benefits from network theory to characterize both physiological and pathological brain networks. However, to date the analysis of such systems still relies on classic approaches, thus limiting the amount of information extracted from those networks. As to overcome such a limitation, this work investigates the behavior of brain networks combinig combining both spectral graph theory and random walk analysis. Specifically, the algebraic connectivity and the relaxation time have been extracted from functional resting state brain networks estimated from a population of subacute post-stroke subjects. Results have been correlated with the Upper Extremity Fugl-Mayer Assessment (UEFMA) score of each subject as to assess whether a dependence exists between network's organization and motor impairment in the upper limb. © 2024 IEEE.

关键词： Network theory (graphs)

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MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution 41

MFTN: A Multi-scale Feature Transfer Network Based on IMatch...

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41st International Conference on Machine Learning, ICML 2024

作者： Huang, Shuying Ren, Mingyang Yang, Yong Wang, Xiaozheng Wei, Yingzhi School of Software Tiangong University Tianjin China School of Computer Science and Technology Tiangong University Tianjin China School of Control Science and Engineering Tiangong University Tianjin China

Hyperspectral image super-resolution (HISR) aims to fuse a low-resolution hyperspectral image (LR-HSI) with a high-resolution multispectral image (HR-MSI) to obtain a high-resolution hyperspectral image (HR-HSI). Due to some existing HISR methods ignoring the significant feature difference between LR-HSI and HR-MSI, the reconstructed HR-HSI typically exhibits spectral distortion and blurring of spatial texture. To solve this issue, we propose a multi-scale feature transfer network (MFTN) for HISR. Firstly, three multi-scale feature extractors are constructed to extract features of different scales from the input images. Then, a multi-scale feature transfer module (MFTM) consisting of three improved feature matching Transformers (IMatchFormers) is designed to learn the detail features of different scales from HR-MSI by establishing the cross-model feature correlation between LR-HSI and degraded HR-MSI. Finally, a multiscale dynamic aggregation module (MDAM) containing three spectral aware aggregation modules (SAAMs) is constructed to reconstruct the final HR-HSI by gradually aggregating features of different scales. Extensive experimental results on three commonly used datasets demonstrate that the proposed model achieves better performance compared to state- of-the-art (SOTA) methods. Copyright 2024 by the author(s)

关键词： Image resolution

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Propagation Characteristics of Partial Discharges in an Oil-Filled Power Transformer 17

Propagation Characteristics of Partial Discharges in an Oil-...

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17th IEEE International Conference on Compatibility, Power Electronics and Power engineering, CPE-POWERENG 2023

作者： Kameli, Sayed Mohammad Refaat, Shady S. Ghrayeb, Ali Abu-Rub, Haitham Guzinski, Jaroslaw Texas AandM University at Qatar Electrical and Computer Engineering Doha Qatar University of Hertfordshire School of Physics Engineering and Computer Science Department of Engineering United Kingdom Gdansk University of Technology Electrical and Control Engineering Faculty ul. Gabriela Narutowicza 11/12 Gdansk80-233 Poland

ISBN: (纸本)9798350300048

Power transformers are among the most important assets in the power transmission and distribution grid. However, they suffer from degradation and possible faults causing major electrical and financial losses. Partial discharges (PDs) are used to identify the insulation health status and their degradation level. PDs are incipient, low-magnitude faults caused by localized dielectric breakdown. Those activities emit signals in many forms, including electrical, chemical, acoustic, electromagnetic, and optical, facilitating various detection methods. This paper provides a theoretical basis for the condition evaluation of an oil-filled power transformer and clarifies the relationship between the operating voltage, void location, and electric-field intensity within the void. This was achieved by investigating the propagation characteristics of partial discharge signals in an oil-filled power transformer using a 3D finite element method (FEM) based simulation. Moreover, the characterization of simulated PD sources at different positions is investigated in this paper. The simulation results are curried out to show that air voids near the windings are subject to greatest peak electric field intensity. © 2023 IEEE.

关键词： Power transformers

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