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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Zhu, Zekun Gong, Ningbo Diao, Guijie Yang, Shunchuan School of Electronic and Information Engineering Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781665442282

A magneto-quasi-static (MQS) surface integral equation (SIE) formulation with loop analysis is proposed to extract the impedance of interconnects in packages. The loop analysis is developed with an independent and complete set of unknowns according to the graph theory, which can significantly reduce the dimension of the final matrix. With the pre-corrected fast Fourier Transform (pFFT), large-scale interconnects can be efficiently modelled. A practical example in packages is carried out to validate the effectiveness and scalability of the proposed formulation. Results show that the proposed formulation is accurate and flexible to model complex interconnects in packages compared with the industrial solver. © 2023 IEEE.

关键词： Fast Fourier transforms

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Flight Parameter Prediction and Fault Propagation based on Machine Learning and Symbolic Directed Graph 6

Flight Parameter Prediction and Fault Propagation based on M...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Li, Wenzhuo Guo, Kun Cheng, Yuehua Hu, Hengsong Xu, Cheng Yu, Ziquan Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Institute of Mechanical and Electrical Engineering Beijing China

ISBN: (纸本)9798350316155

Fault influence and propagation analysis of flight vehicle systems is an important element of flight vehicle health management and also an important problem to be solved. A fault influence model based on data-driven is established, including a prediction model of flight parameters under fault, a dynamic influence path, and an influence degree model. Based on the historical experimental data, a long and short-term memory neural network (LSTM) model is proposed to predict the time-series data of each flight parameter of the flight vehicle under fault;based on the prediction results, a symbolic directed graph (SDG) is used to describe the fault of the flight vehicle system, and then introduce the concept of a compatible path with time-series characteristics to describe the dynamic propagation process of the fault. The case shows that the method proposed in this paper enables qualitative and quantitative analysis of the fault influence, and can reasonably describe the fault propagation path and influence characteristics. © 2023 IEEE.

关键词： Directed graphs

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Distributed Observer-Based Simultaneous Fault Detection and Formation Control of Multi-UAVs 42

Distributed Observer-Based Simultaneous Fault Detection and ...

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42nd Chinese Control Conference, CCC 2023

作者： Su, Xiaowan Hao, Mingrui Yang, Ruohan Yue, Keyuan Feng, Zhichao Northwestern Polytechnical University Xi'an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China The Rocket Force University of Engineering Xi'an710025 China

ISBN: (纸本)9789887581543

This paper studies the formation control and simultaneous fault detection of multi-UAVs. Firstly, a distributed observer is constructed for the second-order particle model of each UAV. Secondly, a novel formation controller is designed based on the distributed observer. Then, the faulty UAV is detected by the residual signal. Finally, based on Lyapunov theory and Projection Lemma, sufficient conditions for UAVs formation are obtained. The effectiveness of the proposed method is verified by simulation. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Fault detection

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MDRN: Multi-distillation residual network for efficient MR image super-resolution

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Mathematical Biosciences and Engineering 2024年第10期21卷 7421-7434页

作者： Deng, Liwei Chen, Jingyi Yang, Xin Huang, Sijuan Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of Automation Harbin University of Science and Technology Heilongjiang Harbin150080 China State Key Laboratory of Oncology in South China Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangdong Provincial Clinical Research Center for Cancer Sun Yat-sen University Cancer Center Guangdong Guangzhou510060 China Guangdong Esophageal Cancer Institute Guangdong Guangzhou510060 China

Super-resolution (SR) of magnetic resonance imaging (MRI) is gaining increasing attention for being able to provide detailed anatomical information. However, current SR methods often use the complex convolutional network for feature extraction, which is difficult to train and not suitable for limited computation resources in the medical scenario. To tackle these bottlenecks, we propose a multidistillation residual network (MDRN) for more differential feature refinement, which has a superior trade-off between reconstruction accuracy and computation cost. Specifically, a novel feature multidistillation residual block with a contrast-aware channel attention module was designed to make the residual features more focused on low-vision information, which maximizes the power of MDRN. Comprehensive experiments demonstrate the superiority of our MDRN over state-of-the-art methods in reconstruction quality and efficiency. Our method outperforms other existing methods in peak signal-noise ratio by up to 0.44-1.82 dB in 4× scale when GPU memory and runtime are lower than in other SR methods. The source code will be available at https://***/Jennieyy/MDRN. © 2024 the Author(s).

关键词： Magnetic resonance imaging

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Optimal Motion Planning for 6-Dof Manipulator Based on Cptdba Algorithm

SSRN

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SSRN 2024年

作者： Huang, Cheng Wang, Tao Xu, Jiazhong Laboratory of Complex Intelligent System and Integration School of Automation Harbin University of Science and Technology Harbin150080 China

Aiming at the optimal motion planning problem of the 6-DOF manipulator in Cartesian space, a motion planning method based on the hybrid bat algorithm (CPTDBA) and 4-3-4 piecewise polynomial interpolation is proposed to plan the optimal motion path of the manipulator end-effector, while optimizing the motion trajectory and motion time that satisfy the motion constraints. Firstly, based on the framework of standard bat algorithm, chaos mapping, adaptive random dynamic perturbation, random exploration mechanism and reverse learning strategy are integrated in initialization, global exploration and local exploitation, and the CPTDBA algorithm is designed to achieve collision-free and shortest path planning of the manipulator end-effector. Secondly, in order to make the planned path smooth and take the shortest time, the optimal movement time of the end-effector is found through the CPTDBA algorithm under the motion constraints of displacement, velocity and acceleration. On this basis, the 4-3-4 piecewise polynomial interpolation algorithm is used to perform path smoothing and time-optimal trajectory planning, and the relevant motion curves of each joint are obtained through the inverse solution. Finally, through simulation comparison with other planning methods and interpolation methods, it is verified that the planned motion path and motion time of this method are relatively optimal, and the optimized motion trajectory is smoother. © 2024, The Authors. All rights reserved.

关键词： Motion planning

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Research on Location Algorithm Based on SAR and Infrared Fusion 1

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yang, Yanjiao Qu, Guangzhou Li, Bo Ma, Meng Liu, ShuaiShuai Chi, QingXi Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Coopration Laboratory Beijing China

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

Aiming at the problem of sins cumulative error correction, a dual-mode navigation algorithm based on infrared and SAR information fusion is studied. Radar system can provide SAR image and range information, and can measure height under certain conditions, but it cannot work in front. Infrared system can provide infrared image and optical axis direction of infrared lens. Based on the satellite positioning algorithm, this paper studies a fusion algorithm of radar SAR image and infrared. The image matching and measurement results are used to navigate to correct the accumulated errors of sins. Simulation results show the effectiveness of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar imaging

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complex-Valued Signal Capsule Network for Automatic Modulation Classification

Complex-Valued Signal Capsule Network for Automatic Modulati...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yang, Shuyuan Feng, Zhixi Wang, Nengguo Bu, Yunong Hu, Hao Luoyang471003 China Xidian University Shannxi China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Most current deep learning (DL) based AMC methods often require a large number of labeled samples to drive itself optimization study, so as to achieve a more superior performance. However, for many AMC tasks with a small amount of data, the AMC method based on deep learning still has many challenges, which makes the deep neural network model trained on a small dataset lack effective migration effect, leading to the failure to achieve better performance effect in the testing process. In this paper, we propose a novel AMC method based on complex-valued Signal Capsule Network (CSCN). Compared with other DL based methods, the proposed CSCN can achieve a better performance under the condition of small dataset and low SNR on the well-known deepsig dataset RML2016.10a and RML2016.10b. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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Design of Reinforcement Learning Environment for Multiple UAV Area Coverage Search

Design of Reinforcement Learning Environment for Multiple UA...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Sun, Yinjiang Zhang, Rui Liu, Xiaoheng Liang, Wenbao Xu, Cheng Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Unmanned aerial vehicle (UAV) plays an increasingly important role both in civil and military fields. As a typical mission, area coverage search is a primary measure for reconnaissance and surveillance of unknown areas. Due to the limited information about the mission area, UAV needs adaptiveness to the dynamic changes of the area and makes decisions based on local observation. It puts higher demands on the response speed of UAV, and traditional planning methods are tough to be directly applied. The problem becomes more noticeable for multiple UAV because of the heterogeneous function and large scale, and new solutions are urgently required. In this paper, the feasibility of reinforcement learning (RL) for performing area coverage search is explored, and an environment is designed for RL training and evaluation. Simulation results show that multiple UAV can cooperate and perform the mission with pretty high coverage. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Adversarial Example Attack and Defence of Object Recognition: A Survey

Adversarial Example Attack and Defence of Object Recognition...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Tan, Wei Zhao, Jiajia Liang, Xinkai Lu, Hanchen Song, Baogang Guan, Hao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Mechano-Electronic Engineering Institute Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Deep learning-based intelligent object recognition algorithm has been widely applied in object detection, auto driving, ect. However, deep neural network is very vulnerable because of its high-dimensional linearization. The object recognition results can be easily mis-leaded through a tiny disturbance in the original image. This kind of sample that adds tiny disturbance to the original image is called adversarial example. The adversarial example attack is a factor that must be considered in the design of robust object recognition algorithm, that is, the need for adversarial defence. An in-depth understanding of adversarial attack can help the model defend successfully. In this survey, an introduction of adversarial attack and defense aiming to object recognition algorithm at the present stage is summarized, and the challenges to be faced and the development trend in the future are pointed out. © 2022 IEEE.

关键词： Object recognition

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Solving Ascent Trajectory Optimization Problems by Radua Pseudospectral Method

Solving Ascent Trajectory Optimization Problems by Radua Pse...

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2022 International Symposium on intelligent Robotics and systems, ISoIRS 2022

作者： Deng, Liaochao Xu, Cheng You, Weishuai Beijing Institute of Mechanical and Electrical Engineering Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665455213

Ascent trajectory optimization problem of air-breathing hypersonic vehicles is a highly nonlinear and nonconvex problems. Most of the early works focus on the traditional indirect method, which needs to derive the complete first-order necessary conditions of the trajectory optimization problem. The derivation process is too complicated and error-prone. Additionally, indirect method has a high demand on the initial guess, and it needs to give the initial guess of covariant variables without physical significance. In this paper, we solve the ascent trajectory optimization problem directly using Radau Pseudospectral Method (RPM). Firstly, the complex three-dimensional ascent trajectory optimization problem is established in detail. Conmmon inequality path constraints including those on dynamic pressure and aerodynamic bending moment are taken into account. The performance index is given as maximizing the final mass considering minimizing the fuel consumption. Subsequently, the ascent trajectory optimization problem is transformed into a nonlinear programming problem (NLP) by RPM. Finally, the ascent trajectory optimization for Generic Hypersonic Aerodynamic Model Example (GHAME) is solved by RPM and the optimal results demonstrate the rapidity, effectiveness and high precision of RPM. The comparison between optimal trajectories with and without path constraints shows that path constraints increase fuel consumption. © 2022 IEEE.

关键词： Hypersonic vehicles

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