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IEEE Transactions on Industrial Cyber-Physical systems 2024年 2卷 143-153页

作者： Xue, Yawen Pan, Jie Geng, Yangyang Yang, Zeyu Liu, Mengxiang Deng, Ruilong Information Engineering University Zhengzhou450001 China Singapore University of Technology and Design ITrust 487372 Singapore The University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS10 2TN United Kingdom Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou313000 China

Industrial control systems (ICSs) are becoming increasingly interconnected as the rapid convergence of information technology (IT) and operation technology (OT) networks, and meanwhile massive attack surfaces have been exposed. However, traditional intrusion detection systems (IDSs) are difficult to be directly deployed in ICSs due to the hard real-time requirement and rare patching chance. Besides, the design of effective and practical IDSs is hampered by the lack of benchmarking ICS cybersecurity datasets. To bridge the gaps, this paper makes the first attempt by open-sourcing the developed ICS cybersecurity datasets and proposing a decision fusion based real-time IDS. Firstly, we design a customized cybersecurity dataset in a full-hardware and high-fidelity platform, including 7 types of cyber threats tailored for ICSs. The collected dataset includes network traffic, sensor readings, actuator status, and system parameters, providing the state-of-the-art benchmark dataset for ICSs consisting of cross-layer characteristics. Furthermore, we design an online decision fusion-based IDS by strategically integrating 4 widely-used machine learning models. The proposed IDS is deployed on a real-time running ethanol distillation, surpassing the performance of single detection models in terms of precision and F1-score, which substantially enhances intrusion detection accuracy and cybersecurity of ICS. © 2023 IEEE.

关键词： Intrusion detection

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Enhancing 3D Human Skeleton Key-point Detection through Weakly Supervised Learning and Multi-level Attention Mechanisms

Enhancing 3D Human Skeleton Key-point Detection through Weak...

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Xu, Meng Gong, Yuanhao Dogramadzi, Sanja University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS10 2TN United Kingdom Shenzhen University Faculty of Electronics and Information Engineering China

ISBN: (纸本)9798350383386

With the soaring interest in understanding the dynamics of human body skeletons for applications such as action recognition and video understanding, the significance of precise 3D key-point detection has become increasingly prominent. Despite the advancements, existing approaches struggle to address the issues of occlusions and limited annotated data. This paper proposes a novel framework integrating a multilevel attention mechanism and weakly supervised 3D key-point generation to tackle these prevalent issues, enhancing both the accuracy and efficiency of human pose estimation. © 2023 IEEE.

关键词： Musculoskeletal system

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RGB-D Image-Based Deep Neural Network Body Shape Classifier

RGB-D Image-Based Deep Neural Network Body Shape Classifier

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

ISBN: (纸本)9798350383386

Leveraging the untapped potential of depth information in RGB-D images, this study introduces a deep neural network classifier for advanced body shape classification. Going beyond traditional RGB image analysis, our method innovatively employs multi-task learning, simultaneously performing body shape classification, posture estimation, and body part segmentation to achieve superior accuracy. This approach promises to revolutionize personalization avenues in healthcare, fashion, and entertainment industries, establishing a new benchmark in body shape analysis. © 2023 IEEE.

关键词： Deep neural networks

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Predictive Norm Optimal Iterative Learning control for High-performance Formation control Problem 63

Predictive Norm Optimal Iterative Learning Control for High-...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Zhang, Yueqing Chen, Bin University of Southampton Faculty of Engineering and Physical Sciences SouthamptonSO17 1BJ United Kingdom University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS10 2TN United Kingdom

ISBN: (纸本)9798350316339

This paper develops a predictive optimisationbased iterative learning control (ILC) strategy for the highperformance formation control problem in networked dynamical systems working repetitively. It avoids the need for exact model information in traditional methods and achieves high performance via a predictive framework incorporating a unique performance index that integrates both immediate and future performance. The proposed framework guarantees geometric convergence of the formation error norm to zero and is capable of handling both heterogeneous and non-minimum phase systems. A distributed implementation of the framework is developed using the Alternating Direction Method of Multipliers to guarantee the framework's scalability for largescale networks. Rigorous convergence analysis and numerical examples are provided to confirm its effectiveness. © 2024 IEEE.

关键词： Predictive control systems

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Adaptability analysis on the measurement device of UACV special machinery unlocking force

Adaptability analysis on the measurement device of UACV spec...

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2023 International Conference on Mechatronic engineering and Artificial Intelligence, MEAI 2023

作者： Yang, Mo Cai, Zizhuo Lin, Jing Li, Jiahao Ren, Haiyue Liu, Qiang School of Mechanical Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing210094 China Department of Automatic Control Systems Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia

ISBN: (纸本)9781510674608

During the unlocking process of the rotating-bolt locking special machinery head, there is a significant resistance. The aim is to select a motor for unmanned aerial combat vehicle (UACV) mounted external power special machinery drives, taking the special machinery unlocking force as the research subject. Adaptive analysis is conducted on the patented structure of the special machinery unlocking force measurement device previously designed. A virtual prototype model is established using the dynamic simulation software ADAMS to apply driving, constraints, and simulation parameters based on the model's principles. Addressing the phenomenon of the detachment of the guide rod slider from the tested bolt carrier during the operation of the special machinery unlocking force measurement device, it is hypothesized that the detachment time is related to the stiffness of the spring and the velocity of the lead screw slider. Through multiple comparative simulations, the correctness of the hypothesis is proven. It is demonstrated that increasing the velocity of the lead screw slider can completely eliminate the detachment time, whereas increasing the stiffness of the spring, although reducing the detachment time, still results in secondary detachment. Consequently, the conclusion is drawn that increasing the velocity of the lead screw slider is the way to resolve the detachment issue of the guide rod slider from the tested bolt carrier in the experiment. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Research on the measurement device of UAV firearm unlocking force 4

Research on the measurement device of UAV firearm unlocking ...

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4th International Conference on Mechanical engineering, Intelligent Manufacturing, and Automation Technology, MEMAT 2023

作者： Yang, Mo Lin, Jing Li, Jiahao Cai, Zizhuo Ren, Haiyue Liu, Qiang School of Mechanical Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing210094 China Department of Automatic Control Systems Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia

ISBN: (纸本)9781510674820

In the current firearms dynamics research, the majority of studies focus on the extraction resistance and subsequent recoil forces, with relatively fewer studies on the unlocking force. This study focuses on the measurement of firearm unlocking force by analyzing the previously designed measurement device. By employing theoretical and dynamic simulation analyses, the variations of unlocking force over time were determined. A comparison of two sets of curves showed a high degree of coincidence, indicating the feasibility of the device in principle. Subsequently, to verify the accuracy of the measurements obtained by the device, a specific firearm was studied through simulation and experimental analysis, demonstrating the precision of the device's measurements. This structural device not only can be effectively used for measuring firearm unlocking force but also provides a new approach for experimental research on this force in firearms. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Enhancing 3D Human Skeleton Key-point Detection through Weakly Supervised Learning and Multi-level Attention Mechanisms

Enhancing 3D Human Skeleton Key-point Detection through Weak...

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Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Meng Xu Yuanhao Gong Sanja Dogramadzi Department of Automatic Control and Systems Engineering University of Sheffield S10 2TN Sheffield Faculty of Electronics and Information Engineering Shenzhen University Department of Automatic Control and Systems Engineering University of Sheffield S10 2TN

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controllable reactor based hybrid HVDC breaker

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High Voltage 2020年第5期5卷 543-548页

作者： Amir Heidary Mehdi Bigdeli Kumars Rouzbehi Department of Electrical Engineering Zanjan BranchIslamic Azad UniversityZanjanIran 2Department of System Engineering and Automatic ControlUniversity of SevilleSevilleSpain

Short circuit fault occurrence in high-voltage DC (HVDC) systems causes extremely high currents in a fast raising time that does not experience current zero-crossing. To protect HVDC systems/grids against fault current, fast HVDC breaker is an essential equipment. This study presents the design procedure of a novel HVDC breaker based on solid-state controllable reactor which is able to reduce the fault current's rate of rise and fault current amplitude to less than grid nominal current in the breaking process. The main achievement of the proposed HVDC breaker is that not only breaker does not encounter fault current, but also none of the series HVDC equipment is influenced by the fault. The designed breaker performance is studied by PSCAD/EMTPS, and then the simulation results are validated by the developed laboratory experimental setup.

关键词： fault EMTP nominal

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Software-defined event-based camera and vision algorithms for digitizing highly dynamic manufacturing tasks

Software-defined event-based camera and vision algorithms fo...

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2024 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2024

作者： Walker, Emily Turner, Christopher J. Oyekan, John Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom Surrey Business School The University of Surrey Surrey GuildfordGU2 7XH United Kingdom Real Time & Distributed Systems Group Department of Computer Science University of York Heslington YorkYO10 5GH United Kingdom

ISBN: (纸本)9781837242672

Event-based cameras are inspired by the way the retina in the eye process information. Rather than capturing image frames at a constant rate, event cameras generate data asynchronously, based on changes in pixel value between frames. As a result, these cameras have a high spatiotemporal accuracy, low power constraints and reduced artefacts from motion blur. Hence, they represent favourable properties for digitizing highly dynamic manufacturing tasks such as machine vibrations and rapid human assembly actions. However, the costs of event-based cameras are prohibitively high for small to medium sized enterprises (SMEs). In this research, we present the development of a rig that combines low-cost visual sensors with low-cost algorithms to perform action recognition for highly dynamic manual manufacturing tasks. We applied our algorithms to achieve an action classification system via a novel threshold-based approach and in parallel use a neural network to perform classification of objects in the video feed. The results achieved demonstrated that our approach was able to successfully identify various rapid manual tasks being performed on identified objects. In addition to SMEs, our approach would be suited for providing low-cost digitization on legacy machines. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/).

关键词： Machine vibrations

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Tracking-in-range Formulations for Numerical Optimal control

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IFAC-PapersOnLine 2024年第18期58卷 53-58页

作者： Nikilesh Ramesh Eric C. Kerrigan Yuanbo Nie Interdisciplinary Programmes in Engineering University of Sheffield S10 2TN Sheffield UK Department of Electrical & Electronic Engineering and Department of Aeronautics Imperial College London SW7 2AZ London UK Department of Automatic Control and Systems Engineering University of Sheffield S10 2TN Sheffield UK

In contrast to set-point tracking which aims to reduce the tracking error between the tracker and the reference, tracking-in-range problems only focus on whether the tracker is within a given range around the reference, making it more suitable for the mission specifications of many practical applications. In this work, we present novel optimal control formulations to solve tracking-in-range problems, for problems requiring the tracker to be always in range, as well as problems allowing the tracker to go out of range, which yield overall better outcomes. Since the problem naturally involves discontinuous functions, we present alternative formulations and regularisation strategies to improve the performance of numerical solvers. The extension to in-range tracking with multiple trackers and in-range tracking in high-dimensional space are also discussed and illustrated with numerical examples, demonstrating substantial increases in mission performance in comparison to traditional set-point tracking.

关键词： Optimal control Nonlinear Model Predictive control Intelligent Vehicles

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