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A Noise-Excitation Generative Adversarial Network for Actuator Fault Diagnosis of Multi-legged Robot

无人系统（英文） 2023年第2期11卷 159-173页

作者： Liling Ma Jian Guo Jiehao Li Junzheng Wang State Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of TechnologyBeijing 100081P.R.China

This research provides a novel approach for detecting multi-legged robot actuator *** most significant concept is to design the Fault Diagnosis Generative Adversarial Network(FD-GAN)to fully adapt to the fault diagnosis problem with insufficient *** found that it is difficult for methods based on classification and prediction to learn failure patterns without enough data.A straightforward solution is to use massive amounts of normal data to drive the diagnostic *** introduce frequency-domain information and fuse multi-sensor data to increase the features and expand the difference between normal data and fault data.A GAN-based framework is designed to calculate the probability that the enhanced data belongs to the normal *** uses a generator network as a feature extractor,and uses a discriminator network as a fault probability evaluator,which creates a new use of GAN in the field of fault *** the many learning strategies of GAN,we find that a key point that can distinguish the two types of data is to use the hidden layer noise with appropriate discrimination as the *** also design a fault location method based on binary search,which greatly improves the search efficiency and engineering value of the entire *** have conducted a lot of experiments to prove the diagnostic effectiveness of our architecture in various road conditions and working *** compared FD-GAN with popular diagnostic *** results show that our method has the highest accuracy and recall rate.

关键词： Actuator fault diagnosis multi-legged robot generative adversarial network attention mechanism

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Cramér-Rao Bound Minimization for a Passive Sensing Multi-ISAC system

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IEEE Transactions on Vehicular Technology 2025年

作者： Chen, Jian Chen, Qikai Deng, Yansha Jia, Jie Yin, Baoxin Wang, Xingwei Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Engineering Research Center of Security Technology of Complex Network System Ministry of Education Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China King's College London LondonWC2R 2LS United Kingdom

The integrated sensing and communication (ISAC) system can simultaneously provide communication and radar sensing, effectively improving spectrum utilization. However, existing research mainly focuses on the mono-static sensing ISAC system, which has shortcomings in limited sensing range and accuracy. We thus investigate a passive sensing multi-ISAC system with multiple communication users and sensing targets, and consider two cases for multi-target sensing without and with prior target knowledge at the base stations (BSs), in which the BSs are interested in estimating the targets' response matrix and channel coefficients, respectively. We also formulate a joint beamforming problem to minimize the Cramér-Rao bound (CRB) of the worst estimation constrained by communication requirements, and obtain the optimal solution with semidefinite relaxation (SDR) assisted transformation. To verify the advantages of our proposed scheme, we consider the bi-static BSs system (B-B) and beamforming with sensing interference cancellation (W-S) as two benchmark schemes. Numerical results illustrate that the proposed scheme obtains better sensing performance and effectively alleviates the effect caused by sensing interference. © 1967-2012 IEEE.

关键词： Cramer-Rao bounds

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Contact Force Optimization to Enhance Fault-tolerant Motion Stability of a Hexapod Robot

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Journal of Bionic Engineering 2024年第5期21卷 2199-2214页

作者： Bo You Shangdong Shi Chen Chen Jiayu Li Nan Li Liang Ding The Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education and the Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

This paper presents a novel method for optimizing the contact force of a hexapod robot to enhance its dynamic motion stability when one of its legs *** proposed approach aims to improve the Force Angle Stability Margin(FASM)and adapt the foot trajectory through contact force optimization to achieve safe and stable motion on various *** foot force optimization approach is designed to optimize the FASM,a factor rarely considered in existing contact force optimization *** formulating the problem of enhancing the motion stability of the hexapod robot as a Quadratic Programming(QP)optimization problem,this approach can effectively address this *** of a hexapod robot using a fault-tolerant gait,along with real field experiments,were conducted to validate the effectiveness and feasibility of the contact force optimization *** results demonstrate that this approach can be used to design a motion controller for a hexapod robot with a significantly improved motion *** summary,the proposed contact force optimization method offers a promising solution for enhancing the motion stability of hexapod robots with single leg failures and has the potential to significantly advance the development of fault-tolerant hexapod robots for various applications.

关键词： Hexapod robot Fault-tolerant Stability margin Contact force optimization

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Color moving object detection method based on automatic color clustering 33

Color moving object detection method based on automatic colo...

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第三十三届中国控制会议

作者： LI Jing WANG Junzheng Mao Jiali Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781479947249

Moving object detection is usually used in gray image, and the color image should be converted to gray images to achieve detection. However, the color object can’t be described by simple gray information completely. In order to achieve automatic color moving object detection, the method based on automatic color clustering is especially proposed. Because the difference between adjacent pixels in an image is very small, the initial cluster center can be moved in the maximum distance. The proposed method can reduce the number of iterations and quicken convergence speed, meanwhile determine the number of color cluster and the location of the color object automatically. The proposed algorithm is validated in the actual system, experimental results show that the proposed method can automatically achieve color clustering for color image, while detect color objects.

关键词： Color clustering Color object Moving object detection

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Dependency-Enhanced Reordering Model for Chinese-English SMT 35

Dependency-Enhanced Reordering Model for Chinese-English SMT

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第35届中国控制会议

作者： WANG Miaomiao XIE Guo DU Jinhua Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

This paper proposes a dependency-enhanced pre-reordering method for Chinese-English statistical machine translation(SMT).Firstly,two kinds of dependency structure-based rules are extracted based on the source-side dependency tree and corresponding word alignments between the source-side and the target-side *** a maximum entropy classifier is used to calculate the orientation probability in terms of swap or monotone between two *** a result,a reordering rule set is *** different ways are proposed to filter out the rule ***,the dependency parsing trees of the training data,development set and the test set are traversed,and if the syntactic sub-tree structure matches the rules in the rule set,the word orders will be ***,a reordered source-side sentence is generated and then fed into an SMT system for *** conducted on NIST Chinese-English MT data sets show that the proposed method significantly improves translation performance by 0.46 BLEU compared to the baseline system.

关键词： Statistical Machine Translation Word Alignment Dependency Syntactic Parsing

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GCN-Transformer Autoencoder with Knowledge Distillation for Unsupervised Video Anomaly Detection

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Journal of Advanced Computational Intelligence and intelligent Informatics 2025年第3期29卷 659-667页

作者： Yan, Mingchao Xiong, Yonghua She, Jinhua School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No.388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Engineering Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo192-0982 Japan

Video anomaly detection is crucial in intelligent surveillance, yet the scarcity and diversity of abnormal events pose significant challenges for supervised methods. This paper presents an unsupervised framework that integrates graph attention networks (GATs) and Transformer architectures, combining masked autoencoders (MAEs) with self-distillation training. GATs are utilized to model spatial and inter-frame relationships, while Transformers capture long-range temporal dependencies, overcoming the limitations of traditional MAE and self-distillation approaches. The model employs a two-stage training process: first, a lightweight MAE combined with a GAT-Transformer fusion constructs a knowledge distillation module;second, the student autoencoder is optimized by integrating a graph convolutional autoencoder and a classification head to identify synthetic anomalies. We evaluate the proposed method on three representative datasets—ShanghaiTech Campus, UBnormal, and UCSD Ped2—and achieve promising results. © Fuji Technology Press Ltd.

关键词： Network coding

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An Online Parameter Estimation Method for a class of Nonlinear systems Based on Particle Filter 34

An Online Parameter Estimation Method for a class of Nonline...

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第三十四届中国控制会议

作者： XIE Guo ZHANG Dan HEI Xinhong QIAN Fucai Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781467374439

Nonlinear system identification is one of the most important topics all over the word. Until now, there are many of off-line identification methods which exhibit well performance. The online approach with non-Gaussian noise, however, is still a challenge. For a class of nonlinear systems where all of the candidate parameters are contained in a definite parameter set, an online parameters and sates estimation method is proposed based on particle filter and Bayes theorem as the following steps. Firstly, regarding all of the candidates, the states are estimated by particle filter(PF) algorithm. Secondly the posterior probabilities of all of candidates are calculated according to the Bayes theorem;then the weights of all of the candidates are obtained through normalization. Lastly, the parameters and sates are estimated ultimately according to the weighted sum of all of the candidates and states. Numerical illustrations are presented to exhibit the application of the method proposed herein, and the performance of the method is examined.

关键词： Nonlinear system,Particle filter,Parameter set,Online parameter identification

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Dynamic image stabilization precision test system based on the Hessian matrix

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Science China(Information Sciences) 2012年第9期55卷 2056-2074页

作者： LI Jing ,WANG JunZheng,WANG ShouKun,MA LiLing & SHEN Wei key laboratory of complex system intelligent control and Decision,School of Automation,Beijing Institute of Technology,Beijing 100081,China 1. Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 China

Dynamic image stabilization precision of an optical image-stable device is a key technical ***,a fast dynamic image stabilization precision test system for an optical image-stable device is developed.A large-aperture collimator with a designed cross divisional board is used to simulate the infinity *** image-stable device is installed on the motion simulator with six degrees of freedom which is used to simulate the moving state of the *** CCD camera installed behind the eyepiece lens of the image-stable device acquires images rapidly and in real *** local energy maxima center of the cross light spot can be acquired accurately through the proposed algorithm using the Hessian *** addition,to deal with the CCD non-uniformity,an adaptive non-uniformity correction algorithm based on bi-dimensional empirical mode decomposition is *** actual test results for the proposed method show that the test error of dynamic image stabilization is less than 0.7,and the time for the frame image acquisition and processing is less than 10 ms,which demonstrates the effectiveness of the test system.

关键词： image stabilization precision adaptive non-uniformity correction empirical mode decomposition local energy maxima Hessian matrix

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Building GIS for Unmanned Ground Vehicles in the Urban Traffic Environment 33

Building GIS for Unmanned Ground Vehicles in the Urban Traff...

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第三十三届中国控制会议

作者： WANG Xinping WANG Meiling ZHANG Yi School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

ISBN: (纸本)9789881563842

As an important research field of intelligent Transport system(ITS),Unmanned Ground Vehicles(UGV)can lessen traffic accidents and relieve traffic congestion by high intelligence,thereby improving the efficiency of the entire *** and more complex urban traffic environment forces UGV to perceive a lot of environmental information,and the Geographic Information system(GIS)has strong capabilities of storage and management for geographic ***,a new method for constructing GIS database is proposed in this paper,which combines the characteristics of urban traffic and needs for perceiving the environment of UGV,to assist UGV in moving in the urban traffic environment ***,Google Earth is used to create the city ***,an urban road network model is proposed and the GIS database of urban traffic environment is constructed based on the ***,the GIS database is used to achieve the least-time route based on improved Dijkstra ***,the GIS database can provide the attributive information of roads in the real vehicle experiment,which guides UGV to perceive the environment *** have shown that the proposed GIS database performs well in assisting UGV to move autonomously in the urban traffic environment.

关键词： GIS,UGV,Urban traffic environment,Database,Road network model

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Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

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Journal of Beijing Institute of Technology 2012年第3期21卷 354-361页

作者：李鹏陈杰蔡涛王光辉 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of EducationBeijing Institute of Technology

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this *** improve the performance,the static neural network and variable neural network are used to build the black-box *** static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required ***,the hybrid dynamic model is validated with a 500 W PEM fuel *** static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

关键词： PEM fuel cell variable neural network hybrid dynamic model

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