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17th International Conference on intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Conditional Disturbance Compensation-Based Fault-Tolerant Group Consensus control for MASs: An Event-Based Switching Method

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IEEE Transactions on Automation science and Engineering 2025年 22卷 13828-13841页

作者： Liu, Pei-Ming Guo, Xiang-Gui Wang, Jian-Liang Che, Wei-Wei Wu, Zheng-Guang University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering Beijing100083 China University of Science and Technology Beijing Shunde Innovation School Foshan528000 China Beihang University Hangzhou Innovation Institute Autonomous Intelligent Systems Department Hangzhou310051 China Northeastern University College of Information Science and Engineering Shenyang266071 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China

With respect to the group consensus control for multi-agent systems (MASs) with disturbances and actuator nonidentical and unknown direction faults (NUDFs), this paper proposes a novel fault-tolerant control scheme by incorporating an event-based switching function and a saturation function. The event-based switching function is implemented to directly switch to the desired working mode, thereby reducing invalid switching after a reverse fault. Concurrently, the saturation function, acting at the software level, can not only prevent the instantaneous impact of excessive reverse input caused by a reverse fault, but also eliminate input peaking and state chattering after switching the working mode. It is worth mentioning that the proposed switching-based fault-tolerant control method can avoid the control chocks and excessive control gains as in the existing methods by using Nussbaum functions and thus improve the transient performance. Additionally, for disturbances, the designed conditional disturbance compensation mechanism ensures a smaller steady-state error, and less energy consumption by utilizing beneficial disturbances and compensating for harmful ones. Besides, the conditional compensation mechanism also reduces the saturation error. Finally, the effectiveness of the proposed control scheme are verified through a simulation example of uncrewed aerial vehicles (UAVs). © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Modified smoothing-homotopy-based sequential convex programming for ascent trajectory optimization with path constraints

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Acta Astronautica 2025年 234卷 632-643页

作者： Mengxin Zhao Binfeng Pan Shan Lu Xiyu Hou School of Astronautics Northwestern Polytechnical University Xi’an 710072 Shaanxi China Shanghai Key Laboratory of Space Intelligent Control Technology Shanghai Aerospace Control Technology Institute Shanghai 201109 China

To meet the growing demands for reliability and onboard performance in launch missions, this paper introduces a modified smoothing-homotopy sequential convex programming (MSH-SCP) approach for endo-atmospheric ascent trajectory optimization problems with strict path constraints. Compared to the original SH-SCP, the proposed method introduces three major enhancements. Firstly, the convolution of the smoothing kernel is extended from the terminal state to all discrete states across the entire time domain. This alleviates the challenges posed by non-convexity in highly nonlinear ascent problems, resulting in an easier and more tractable smoothed problem. Secondly, by replacing states in path constraints with smoothed states, this method eliminates the need to transform path constraints into control constraints, allowing state constraints to be handled directly. Lastly, the continuous-time problem is discretized into a sequence of finite-dimensional sub-problems by parameterizing state and control variables using non-uniform rational basis spline (NURBS) curves. Leveraging from the superior fitting characteristics and strong convex hull properties of NURBS curves, optimization variables and constraints are reduced in number, markedly enhancing computational speed. Numerical simulations reveal that the MSH-SCP method achieves superior convergence behavior and exhibits significant improvements in computational efficiency.

关键词： Convex optimization

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Robust Multi-agent Federated Reinforcement Learning for Task Offloading 7th

Robust Multi-agent Federated Reinforcement Learning for Task...

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7th International Conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Yan, Dibao Wang, Yongfeng Hou, Wenjing Song, Huanhuan Wen, Hong Ma, Wendi Sun, Fan School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China Sichuan Intelligent IoT Communication Technology Engineering Research Center UESTC Chengdu China

ISBN: (纸本)9789819624089

With the proliferation of various mobile smart devices, edge computing and computational offloading technologies have emerged as pivotal support mechanisms, enhancing the service quality of these devices. To facilitate the learning of task offloading strategies across diverse and complex scenarios, this study introduces a federated learning strategy algorithm based on multi-agent deep reinforcement learning. This algorithm aims to aggregate the training strategies of multiple edge computing devices, thereby enabling the synthesis of superior task offloading strategies tailored to a wide array of environments while also providing safeguards against malicious nodes. This paper specifically examines the reward inversion attack, illustrating the algorithm’s capability to identify and counteract such malicious threats effectively. Experimental results validate that the proposed algorithm not only robustly defends against these attacks but also adeptly learns the task offloading strategies pertinent to each node. © The Author(s) 2025.

关键词： Federated learning

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An Offline Learning-Based Anti-interference Communication Scheme for UAV Networks 7th

An Offline Learning-Based Anti-interference Communication Sc...

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7th International Conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Tang, Tao Zhao, Runhui Wen, Hong Feng, Xuewei Shi, Weihong Peng, Yulin School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China Sichuan Intelligent IoT Communication Technology Engineering Research Center UESTC Chengdu China

ISBN: (纸本)9789819624089

Unmanned Aerial Vehicles (UAV) face challenges from advanced interference technologies, making them susceptible to malicious node attacks, data interception, and tampering. Traditional anti-interference decisions have limitations, as they cannot adaptively adjust to changes in interference signals. Moreover, anti-interference communication models based on Deep Reinforcement Learning (DRL) require prolonged interactions with the environment, demanding high requirements for anti-interference environments. This paper investigates an offline anti-interference decision based on Decision-Transformers, which can quickly and stably acquire practical anti-interference decision models. Simulation experiments have verified the effectiveness of this algorithm in making anti-interference decisions under AWGN and fading channel conditions. Furthermore, this offline approach can achieve the expected reward targets with fewer training iterations. © The Author(s) 2025.

关键词： Deep reinforcement learning

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Adaptive Communication Spectrum Sensing Algorithm Based on Energy Detection 7th

Adaptive Communication Spectrum Sensing Algorithm Based on E...

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7th International Conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Shi, Weihong Tang, Tao Zhao, Runhui Wen, Hong Feng, Xuewei School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China Sichuan Intelligent loT Communication Technology Engineering Research Center UESTC Chengdu China

ISBN: (纸本)9789819624089

Based on the traditional energy detection algorithm, an adaptive communication spectrum sensing algorithm based on energy detection is proposed for signals whose noise power is difficult to be estimated accurately. The algorithm takes into account the problem of large error in calculating the energy detection judgment threshold by noise power when the estimated value of noise power is inaccurate, and is able to perform adaptive communication spectrum sensing for signals with less a priori information and noise power that cannot be estimated accurately. Simulation results show that the adaptive communication spectrum sensing algorithm based on energy detection can effectively improve the performance of spectrum sensing for signals, and the algorithm can effectively detect and sense signals under the condition of reasonable setting of judgment coefficients. © The Author(s) 2025.

关键词： Adaptive Cognitive radio Energy detection Spectrum sensing

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The Slippage Model of Outer Ring Faults in Deep Groove Ball Bearings Induced by Impact Forces Under Load

The Slippage Model of Outer Ring Faults in Deep Groove Ball ...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Wu, Yangbiao Zhang, Chao Liu, Guiyi Wu, Le Ouyang, Bing Qin, Feifan School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems in Inner Mongolia Autonomous Region Baotou014010 China

ISBN: (纸本)9783031734069

The study of fault mechanisms plays a crucial role in the field of fault diagnosis. The phenomenon of rolling element slippage is inevitable. In order to more accurately describe the phenomenon of rolling element slippage in the defective area, this paper employs the instantaneous center method and the theorem of three centers to represent the centerline velocity of the rolling element. Due to the change in linear velocity when the rolling element slips, the magnitude of the impact force is calculated according to the principle of collision. Finally, focusing on deep groove ball bearings as the research object, a fault dynamic model is established to simulate the slippage of the rolling element after being subjected to impact force in the defective area. The model is solved using the fourth-order Runge-Kutta method, and the results are simulated. Through experimental simulation analysis, the fault characteristic frequencies obtained from the proposed model are compared with theoretical values, with errors falling within the range of 1 to 2 Hz. Therefore, this provides preliminary validation of the correctness of the proposed model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep groove ball bearings

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Fully Distributed Output Regulation of Linear Discrete-Time Multi-Agent Systems With Markov Switching Topology

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IEEE Transactions on Circuits and Systems I: Regular Papers 2025年 1-9页

作者： Liu, Jiamin Li, Zhao-Yan Zhou, Bin Jimei University School of Science Xiamen361021 China Harbin Institute of Technology School of Mathematics Harbin150001 China Zhengzhou Research Institute of HIT Zhengzhou450000 China Harbin Institute of Technology Center for Control Theory and Guidance Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China

This paper studies the stochastic cooperative output regulation problem for linear discrete-time multi-agent systems (MASs) with Markov switching topologies and communication/input delays. First, a moment stability criterion for an interconnected time-homogeneous Markov jump linear systems is builded. Then, based on the moment stability criterion, a fully distributed output regulation protocol is designed to solve the stochastic cooperative output regulation problem successively. Finally, a numerical simulation is provided to validate the efficiency of the designed protocol. © 2004-2012 IEEE.

关键词： Topology

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FPGA-based Real-time High-resolution Image Processing for rocket on-board processing

FPGA-based Real-time High-resolution Image Processing for ro...

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International Conference on Computer Research and Development (ICCRD)

作者： Hui Zhou Xiaofeng Wang YuJia Xie Yongxiang Cao Yu Tang Yongchun Huo Huan Wen Xiongbo Zhao Chaoran Li Beijing Aerospace Automatic Control Institute National key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China Computer Science and Engineering Beihang University Beijing China National Superior College for Engineers Beihang University Beijing China

ISBN: (数字)9798331531881

ISBN: (纸本)9798331531898

The structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. This paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. This approach yields a 1.29x improvement in computing unit utilization compared to state-of-the-art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. The overall computing efficiency, excluding the first layer, exceeded 90%. The peak computing power for the four cores reached 1638.4 GOPS, and the end-to-end computation time for

关键词： YOLO Rockets Power demand Convolution Multicore processing Reviews Scalability Accelerator architectures Real-time systems Field programmable gate arrays

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Flame Retardancy of Additively Manufactured Carbon Fiber Reinforced ABS Composites with Expandable Graphite Coating

Flame Retardancy of Additively Manufactured Carbon Fiber Rei...

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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Xu, Sida Ren, Zefu Yang, Zhuoyuan Chen, Leitao Reed, Nicholas Govindarajan, Rishikesh Srinivasaraghavan Cheng, Meng Kim, Daewon Jiang, Yizhou Department of Aerospace Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science Hubei Wuhan430081 China

ISBN: (纸本)9781624107238

The development of the 3D printing technique enables additive manufacturing of carbon fiber reinforced thermoplastic composites. However, the existing material design of additively manufactured carbon fiber composites has significant limitations for use under flame-hazardous environments. Herein, we report a flame-retardant coating method as a facial post-processing method for additively manufactured fiber composites. The flame-retardant coating is mainly composed of expandable graphite, and the coating process is via molding. The mechanical properties, thermal properties, and stability of the uncoated and coated samples are analyzed. The fire resistance performance of the additively manufactured composite is demonstrated, and the results reveal that the proposed coating method profoundly increased the fire resistance, toward future flame-retardant composite for aerospace applications. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Flame resistance

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