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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Shi, Liheng Zhang, Jinxu Gu, Yingying Gai, Fangqin Liu, Jing Wu, Guanhao Tsinghua University State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Beijing100084 China Yangtze Delta Region Institute of Tsinghua University Zhejiang Research Center of Opto-electronic Sensing Zhejiang 314006 China Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab. Beijing100190 China China Academy of Space Technology National Key Laboratory of Space Intelligent Control Beijing100094 China

We introduce a method for measuring three degrees of freedom using low-coherence light and temporal phase-shifting to discern position and orientation from the coherence envelope shape, enabling direct measurement wit... 详细信息

ISBN: (纸本)9798350372076

关键词： Degrees of freedom (mechanics)

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A Graph Transformer-Driven Approach for Network Robustness Learning

arXiv

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arXiv 2023年

作者： Zhang, Yu Li, Jia Ding, Jie Li, Xiang The Adaptive Networks and Control Lab Department of Electronic Engineering School of Information Science and Engineering Fudan University Shanghai200433 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China

Learning and analysis of network robustness, including controllab.lity robustness and connectivity robustness, is critical for various networked systems against attacks. Traditionally, network robustness is determined by attack simulations, which is very time-consuming and even incapable for large-scale networks. Network Robustness Learning, which is dedicated to learning network robustness with high precision and high speed, provides a powerful tool to analyze network robustness by replacing simulations. In this paper, a novel versatile and unified robustness learning approach based on the customized graph transformer (NRL-GT) is proposed, which consists of a particularly designed backbone and three branches to accomplish the tasks of robustness curve learning, overall robustness learning and synthetic network classification simultaneously. Numerous experiments show that: 1) NRL-GT is a unified learning framework for controllab.lity robustness and connectivity robustness, demonstrating a strong generalization ability to ensure high precision when training and test sets are distributed differently;2) It is theoretically and experimentally demonstrated the proposed graph transformer layer is capable of outperforming classical graph neural networks. Compared to the cutting-edge methods in network robustness learning, NRL-GT can simultaneously perform network robustness learning from multiple aspects and obtains superior results in less time on both synthetic and real-world networks, especially circuit networks and power networks;3) It is worth mentioning that with the transferability of the proposed backbone, NRL-GT is able to deal with complex networks of different sizes for different tasks efficiently and effectively. Copyright © 2023, The Authors. All rights reserved.

关键词： controllab.lity

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Sliding-Mode Based Fixed-Time control of Takagi-Sugeno Fuzzy systems 36

Sliding-Mode Based Fixed-Time Control of Takagi-Sugeno Fuzzy...

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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Chen, Xili Wang, Leimin Tan, Xingxing China Univ. of Geosci. Hubei Key Lab. of Adv. Control and Intelligent Automation for Complex Systems School of Automation Wuhan430074 China

ISBN: (纸本)9781665437127

In this paper, the fixed-time stabilization of Takagi-Sugeno (T-S) fuzzy system with discrete time delays and external disturbances is investigated via sliding-mode control. Firstly, a suitable controller and sliding-mode surface are designed. After that, by means of Lyapunov functions and inequality technique, state variables of T-S fuzzy system can achieve the designed sliding-mode surface in a fixed time, then keep on it. Finally, the validity of theoretical results is supported by two numerical examples. © 2021 IEEE.

关键词： Fuzzy systems

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Physical layer security verification system based on software defined radio 4

Physical layer security verification system based on softwar...

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4th International Conference on Computer Science and Communication Technology, ICCSCT 2023

作者： Liu, Yonghuang Song, Huanhuan Wen, Hong Yu, Ziyang Li, Wen School of Aeronautics and Astronautics University of Electronic Science and Technology of China Sichuan Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China

ISBN: (纸本)9781510671232

Compared with traditional encryption technology, physical layer security technology uses channel noise to realize the key with the same length as plaintext. Even if the eavesdropper has strong cracking computing power, it cannot decipher the confidential data without the key, which can truly realize "One-Time-Pad" and ensure the security of wireless communication. In this paper, we propose a physical layer security verification system based on software defined radio. In the system, base stations and legitimate users can obtain channel information efficiently, and eavesdroppers can use the powerful storage and computing resources of the cloud server to decrypt confidential signals without time constraints. Based on the system, this paper designs and verifies the physical layer security scheme with joint precoding and Artificial Noise, which fills the gap of the prototype verification platform of information-theoretic security and provides strong support for verifying the unconditional security features of the physical layer security technology. © 2023 SPIE.

关键词： Verification

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Research on Data-Driven Fault Diagnosis of Aero-Engine Transmission systems 42

Research on Data-Driven Fault Diagnosis of Aero-Engine Trans...

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42nd Chinese control Conference, CCC 2023

作者： Ma, Song Yu, Xin-Meng Sun, Tao Zhao, Guang Guo, Mei Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tsinghua University Department of Automation Beijing100084 China School of Energy and Power Engineering Dalian University of Technology Dalian116024 China Avic Shenyang Engine Design Institute Shenyang110066 China

ISBN: (纸本)9789887581543

In this brief paper, a data-based method on the fault diagnosis in aero-engine transmission systems is developed. Firstly, during the operation of splines, we acquire the acceleration vibration signal. We process the signal into time-frequency images using the short-time Fourier transform. Then, the improved convolutional neural network with channel attention is trained using time-frequency images of multiple fault signals. Finally, we implement fault prediction for spline wear and misalignment faults in aero-engine transmission systems. The result shows that the fault diagnosis using the proposed method has a high level of accuracy. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Failure analysis

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Influence of the load variations on the PSS performance during steady state and transient state

Influence of the load variations on the PSS performance duri...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Wassan Adnan Hashim Jawad Hamad Hameed Nabil Derbel Department of Technical Computer Engineering Al-Qalam University College Kirkuk Iraq University of Sfax National Engineering School of Sfax Control & Energy Management Lab. Tunisia Department of Petroleum Systems Control Engineering College of Petroleum Processes Engineering Tikrit University Iraq University of Sfax National Engineering School of Sfax Control & Energy Management Lab. Sfax Tunisia

The load on a power station varies from time to time due to uncertain demands of the consumers and is known as variable load on the station. Also it is known to have an effect on the performance of a power system stabilizer while damping inter-area oscillation. In this paper conventional lead lag PSS and PSS2B are assessed on real case studies; Peerdawod Gas power station in north of Iraq- Erbil. The PSS utilizes the local rotor speed and power as its input. To investigate the effects of dynamic loads on power systems stability, the effectiveness of PSS is tested and compared with the variation of loads during and after sadden faults. The simulation software that used Matlab.M/Simulink; and results of this paper contribute to the understanding of how load variations influence the system damping based on PSS.

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USRP-based real-time experimentation platform for artificial-noise-aided MIMO system 4

USRP-based real-time experimentation platform for artificial...

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4th International Conference on Computer Science and Communication Technology, ICCSCT 2023

作者： Yu, Ziyang Song, Huanhuan Wen, Hong Liu, Yonghuang Li, Wen Hou, Wenjing School of Aeronautics and Astronautics University of Electronic Science and Technology of China Sichuan Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China

ISBN: (纸本)9781510671232

Artificial noise, as a physical layer security technique, differs from traditional communication security mechanisms based on cryptography as it cannot be easily cracked by rapidly developing computational power. The theoretical research on the security of artificial-noise-assisted MIMO (Multiple-Input Multiple-Output) communication systems is quite comprehensive. However, the practical effectiveness of artificial noise in real-world systems still needs to be further validated through experimentation. This paper proposes a real-time platform for simulating experiments on MIMO communication systems assisted by artificial noise. By analyzing experimental data, it demonstrates that artificial noise has a slight impact on the reliability of legitimate MIMO communication systems while effectively enhancing system security. © 2023 SPIE.

关键词： MIMO systems

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Improving Motor Imagery Classification in BCI systems Using EMD and Multi-Layer CNNs

Improving Motor Imagery Classification in BCI Systems Using ...

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International eConference on Computer and Knowledge engineering (ICCKE)

作者： Reza Arghand Ali Chaibakhsh Moein Radman Intelligent Systems and Advanced Control Lab Faculty of Mechanical Engineering University of Guilan Rasht Guilan Iran Brain-Computer Interfacing and Neural Engineering Laboratory University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom

ISBN: (数字)9798331511272

ISBN: (纸本)9798331511289

Brain-Computer Interface (BCI) systems are relatively new technologies that could play a significant role in aiding the recovery of impaired activities resulting from neuromuscular disabilities in affected individuals. Accurate recognition and classification of motor imagery in BCI systems present a challenge, leading to extensive research in recent years aimed at improving the accuracy of these systems. In this study, a combination of the Empirical Mode Decomposition (EMD) method and a multi-layer Convolutional Neural Network (CNN) is employed. Initially, the signal is decomposed into Intrinsic Mode Functions (IMFs) using EMD, and all IMFs across all trials are analyzed to select the best ones, which are then fed into the CNN as inputs. Additionally, the study incorporates the fusion of three CNN networks, each corresponding to a different IMF. The features extracted from these networks are combined and used to train an SVM classifier. The proposed method achieved an accuracy of 86.1% on the BCI-2a 2008 dataset, outperforming other state-of-the-art approaches.

关键词： Support vector machines Knowledge engineering Accuracy Image recognition Empirical mode decomposition Neuromuscular Motors Feature extraction Brain-computer interfaces Convolutional neural networks

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Cooperative Nonlinear Aircraft Defense Using Super Twisting Algorithm with State Constraints

Cooperative Nonlinear Aircraft Defense Using Super Twisting ...

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IEEE Conference on Decision and control

作者： Bhagyashri Gurjar Shashi Ranjan Kumar Dwaipayan Mukherjee Department of Aerospace Engineering Intelligent Systems & Control Lab Indian Institute of Technology Bombay Mumbai India Department of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

This paper addresses the problem of cooperative guidance design for aircraft defense systems involving a target, a defender, and an attacker, using a super-twisting algorithm and barrier Lyapunov function. The system dynamics involve unknown functions, which are treated like disturbances and estimated using an observer. Imposing practical assumptions on the lateral accelerations of the vehicles, we propose a robust guidance design also to constrain the system states by definite bounds. We derived the controller using generalized triangle guidance concepts that provide these bounds for the states. Guidance commands are derived without any kind of linearizations that enable a wider domain of applicability of the proposed approach. The convergence is analyzed using a Lyapunov function. Simulation results are presented to study the efficacy of the proposed approach.

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SA-U-Net++: SAR marine floating raft aquaculture identification based on semantic segmentation and ISAR augmentation

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Journal of Applied Remote Sensing 2021年第1期15卷

作者： Wang, Deyi Han, Min Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Ganjingzi District Dalian China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Ganjingzi District Dalian China

Marine floating raft aquaculture (FRA) monitoring is vital for environment protection and mariculture management. Synthetic aperture radar (SAR) could provide high-quality remote sensing images under all weather conditions compared with the existing optical remote-sensing-based methods. Traditional SAR monitoring methods extract the pixel feature of marine FRA in single patches, which commonly leads to poor generalization. We propose a self-Attention semantic segmentation method based on modified U-Net++ (SA-U-Net++) for FRA segmentation, which could automatically extract semantic feature information, and provide superior performance under complicated scenes. The proposed self-Attention backbone could help to extract more precise features and enhance the overall accuracy. Furthermore, we propose a FRA-ISAR data generation method based on inverse SAR (ISAR) imaging to alleviate the sample shortage problem. We introduce the semantic segmentation method into FRA-SAR segmentation for the first time. The experiments verify the effectiveness and superiority of SAR FRA segmentation based on the proposed SA-U-Net++ model compared with the existed semantic segmentation approaches. © 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Deep learning

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