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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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Multi-OP: A Multilevel Model for Orbital Prediction Using Multi-Feature Fusion 13

Multi-OP: A Multilevel Model for Orbital Prediction Using Mu...

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13th International Conference on intelligent control and Information Processing, ICICIP 2025

作者： Chu, Qinghao Wang, Zhelong Jiang, Yu Hou, Pengrong Zhang, Pinliang School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Astronautic Dynamics Xi’an Satellite Control Center Xi’an China Beijing Institute of Spacecraft Environment Engineering China Academy of Space Technology Beijing China

ISBN: (纸本)9798331516147

To address the increasing computational demands and the need for enhanced stability in the orbit prediction of large-scale resident space objects (RSOs), this paper proposes a novel method grounded in orbital dynamics, which defines and computes environmental, dynamical, and fingerprint features. A feature fusion strategy is then applied to introduce a Multi-OP model comprising a shared backbone and a prediction layer tailored for orbit prediction tasks. Specifically, the shared backbone integrates environmental and dynamical features to capture public information, thereby enhancing the model’s generalization ability. The prediction layer, in contrast, leverages fingerprint features to generate individualized orbit predictions for each RSO. Experimental results demonstrate that the Multi-OP model not only enhances the accuracy of orbit prediction but also exhibits remarkable stability. © 2025 IEEE.

关键词： Prediction models

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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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Research Progress and Prospect of High-Speed Vehicle control technology Based on Reinforcement Learning

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Advances in Astronautics 2025年 1-9页

作者： Lu, Kunfeng Wang, Weili Liu, Xiaodong Huang, Wanwei Jia, Chenhui Yu, Yue Beijing Aerospace Automatic Control Institute Beijing China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China

High reliability and intelligence mark the cutting-edge development trend of high-speed vehicle control technology. This research focuses on the progress of high-speed vehicle control technology based on reinforcement learning, and sorts out its application in control parameter tuning, compensation control, and end-to-end control. Focusing on the development framework of intelligent control safety and efficiency, this paper deeply analyzes the challenges of safety, training efficiency, and interpretability faced by high-speed vehicle in reinforcement learning control, and proposes feasible paths and development directions for future research.

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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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Effect of IQ Imbalance on Cooperative Jamming Cancellation for 6G Security in Physical Layer

Effect of IQ Imbalance on Cooperative Jamming Cancellation f...

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IEEE Conference on Wireless Communications and Networking

作者： Mingyue Jin Wenbo Guo Hongzhi Zhao Shihai Shao National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

While 6G provides communication services for massive wireless devices, it faces huge security risks due to its open feature. Cooperative jamming techniques in physical layer security provide a viable way to ensure 6G security. By actively transmitting jamming signals to deteriorate the eavesdropping channel, while authorized receivers implement cooperative jamming cancellation (CJC) using the prior knowledge of cooperative jamming, thus securing the communication at the physical layer. In practice, incomplete matching of oscillator device characteristics will lead to the in-phase and quadrature (IQ) imbalance problem, where the quadrature branches of the up and down converted carrier signals are not perfectly orthogonal to the in-phase branches, which may degrade the CJC performance. For this reason, this paper specifically analyzes the impact of the IQ imbalance problem on the CJC performance, where a closed-form expression of the jamming cancellation ratio (JCR) with respect to amplitude imbalance and phase imbalance is derived. The simulation results show that when jamming-to-noise ratio (JNR) is 35 dB, the system can tolerate up to 1% amplitude imbalance and 1° phase imbalance with 3 dB JCR degradation. Moreover, the IQ imbalance has a noticeable effect on the reachable security rate of the communication system.

关键词： 6G mobile communication Wireless communication Performance evaluation Simulation Receivers Physical layer security Security Jamming Oscillators Faces

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Dual-modal Motion of Magnetically controlled Soft Microrobots with Environmentally Responsive Reversible Deformation 24

Dual-modal Motion of Magnetically Controlled Soft Microrobot...

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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Xin, Zhengyuan Wu, Anping Bai, Kailun Yang, Haotian Lin, Kaijun Shi, Qing Wang, Huaping Hou, Yaozhen Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Science and Technology on Space Physics Laboratory Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9798400710681

Soft microrobots have garnered attention in the biomedical field due to their ability to access hard-to-reach regions within living organisms for precise manipulation. However, the inability to alter the stable morphology after design and fabrication remains a pressing issue for existing soft microrobots. This limitation results in a fixed range of locomotion modes, thereby restricting the diversity of operational environments. Addressing this challenge, this study proposes and designs a biocompatible X-shaped soft microrobot that achieves alterable stable morphologies through an innovative mechanism. We developed a deformable soft hydrogel robot based on alginate gel’s ability to reversibly swell in response to ion concentration changes. Based on the deformation characteristics of this microrobot, we have designed undulating and rolling locomotion modes that are suitable for different morphologies, along with their corresponding magnetic field manipulation systems, enabling multi-morphology locomotion of the robot. Experimental validations demonstrate that the designed flexible microrobot can achieve a deformation deflection angle of up to 150° under manipulation. This robot not only performs forward undulating locomotion in its expanded state but also executes rolling motion in its spherical configuration, exhibiting high locomotion flexibility and adaptability. © 2024 Copyright held by the owner/author(s).

关键词： Microrobots

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