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Prognostics and system Health Management Conference (PHM)

作者： Xiaoyun Gong Mengxuan Hao Chuan Li Wenliao Du Yixiang Huang Henan International Joint Laboratory of Complex Mechanical Equipment Intelligent Monitoring and Control Zhengzhou University of Light Industry Zhengzhou China Research Center for System Health Maintenance Chongqing Technology and Business University Chongqing China The State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

While existing flow-based models have the potential for data enhancement and intelligent fault diagnosis of bearings, these methods are mainly based on the time domain to learn features. In general, time-domain and frequency-domain features are important for recognizing faults. Especially, the spectral features in the frequency domain can reveal highly distinct patterns associated with fault types. Therefore, learning spectral feature helps to obtain comprehensive fault information and achieve high fault diagnosis accuracy. In this work, a spectral flow model framework is developed to learn and generate realistic data from mechanical sensor signals. The performance of fault diagnosis under unbalanced data is improved by learning the information contained in the spectral features, which are utilized to generate insufficient fault data. Experimental results show that the present method can generate a large number of samples with higher similarity and better diversity on the bearing dataset. The generated samples may be used to expand the limited dataset and significantly improve the accuracy of the bearing fault diagnosis task.

关键词： Fault diagnosis Mechanical sensors Vibrations Training Accuracy Frequency-domain analysis Training data

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Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment 39

Target Assignment Optimization of Heterogeneous Sensor Netwo...

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39th Chinese control Conference, CCC 2020

作者： Chen, Chen Zihao, Cheng Wei, Xu Beijing Institute of Technology School of Automation Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China

ISBN: (纸本)9789881563903

Preventing and controlling Low-Slow-Small(LSS) targets are problems to be solved due to their good concealment in urban environment. Consequently, the problem of target assignment is studied in this paper. Firstly, a target assignment model based on heterogeneous sensor networks is proposed. The characteristics of LSS targets and the influence of environmental factors such as climate and terrain are considered on this model. At the same time, the detection capabilities of different detection nodes and collaborative tracking capabilities are also considered. Secondly, an intelligent optimization algorithm GSAPSO based on PSO is proposed to maximize tracking effect of the sensors. Finally, the simulations are used to compare the GSAPSO algorithm with the traditional PSO and GAPSO algorithms. The results demonstrate that the proposed algorithm has better tracking effect. © 2020 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Particle swarm optimization (PSO)

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Analysis of OODA Loop based on Adversarial for complex Game Environments

arXiv

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arXiv 2022年

作者： Lu, Xiangri Ma, Hongbin Wang, Zhanqing State Key Laboratory of Intelligent Decision Control for Complex Systems Beijing Institute of Technology Beijing China Automated Institute Beijing Institute of Technology Beijing China

To address the problem of imperfect confrontation strategy caused by the lack of information of game environment in the simulation of non-complete information dynamic countermeasure modeling for intelligent game, the hierarchical analysis game strategy of confrontation model based on OODA ring (Observation, Orientation, decision, Action) theory is proposed. At the same time, taking into account the trend of unmanned future warfare, NetLogo software simulation is used to construct a dynamic derivation of the confrontation between two tanks. In the validation process, the OODA loop theory is used to describe the operation process of the complex system between red and blue sides, and the four-step cycle of observation, judgment, decision and execution is carried out according to the number of armor of both sides, and then the OODA loop system adjusts the judgment and decision time coefficients for the next confrontation cycle according to the results of the first cycle. Compared with traditional simulation methods that consider objective factors such as loss rate and support rate, the OODA-loop-based hierarchical game analysis can analyze the confrontation situation more comprehensively. © 2022, CC BY.

关键词： decision theory

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Valuing Equity-Linked Guaranteed Minimum Death Benefits with European-Style Asian Payoffs Under the Regime-Switching Diffusion Process with Jump

SSRN

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SSRN 2022年

作者： Wang, Yayun Liu, Shengda Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

In this paper, we consider a novel and efficient method to price equity-linked guaranteed minimumdeath benefits (GMDB) with European-style geometric Asian and arithmetic Asian payoffs. In thesituation of continuous transition of market economy, we assume that the underlying asset price processfollows regime-switching Ĺevy model and use complex Fourier series (CFS) expansion method to derivethe approximate value of GMDB products. The error analysis shows an exponential convergence rateunder geometric Asian and arithmetic Asian payoffs. Furthermore, the CFS approach is comparedwith other Fourier transform methods and Monte Carlo simulation, the numerical experiment resultsillustrate our method has a distinct advantage over other methods in both efficiency and accuracy. © 2022, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Optimal Switching Integrity Attacks on Sensors in Industrial control systems

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Journal of systems Science and complexity 2019年第5期32卷 1290-1305页

作者： Wu, Guangyu Sun, Jian The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China

In this article, an optimal switching integrity attack problem is investigated to study the response of feedback control systems under attack. The authors model the malicious attacks on sensors as additive norm bounded signals. The authors consider an attacker who is only capable of launching attacks to limited number of sensors once a time and changing the combinations of attacked sensors all over the time. The objective of this paper is to find the optimal switching sequence of these combinations and the optimal attack input. The authors solve this problem by transforming it into a traditional optimal control problem with new control variables vary continuously in the range [0, 1]. The optimal solutions of the new control variables are of bang-bang-type. Therefore, an algebraic switching condition and an optimal attack input can be obtained. Finally, numerical results are provided to illustrate the effectiveness of the methods. © 2019, The Editorial Office of JSSC & Springer-Verlag GmbH Germany.

关键词： Adaptive control systems

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A Multi-Robot Task Allocation Method Based on Graph Attention Network and Unsupervised Learning

A Multi-Robot Task Allocation Method Based on Graph Attentio...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Zirui Wu Zhen Li Dong Zhu Qiuhan Liao Weiran Yao School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China Chengdu CHG Robots & Intelligent Equipment Institute Co. Ltd Chengdu China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

The task allocation for multiple robots is a critical component in the coordination of unmanned clusters. The existing heuristic algorithms are hard to achieve satisfactory results in large-scale problems, and reinforcement learning-based methods face challenges in ensuring the rationality of reward design. This paper introduces a model based on multi-head attention and graph neural networks to address the schedule-dependent multi-robot task allocation problem, trained using unsupervised learning techniques. This model can be trained with varying numbers of robots and tasks without necessitating changes to its structure or parameters. In the experiment of this paper, the model is trained under two different conditions, and the performance is evaluated across six different problem scales. Comparing the proposed model against greedy algorithms and genetic algorithms, the results demonstrate that the proposed model has sianiflcant advantages in overall performance.

关键词： Greedy algorithms Robot kinematics Heuristic algorithms Computational modeling Reinforcement learning Graph neural networks Resource management Unsupervised learning Faces Genetic algorithms

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Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

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arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Magnetically Driven Soft Continuum Microrobot for Intravascular Operations in Microscale

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Cyborg and Bionic systems 2022年第1期2022卷 265-272页

作者： Dan Liu Xiaoming Liu Zhuo Chen Zhaofeng Zuo Xiaoqing Tang Qiang Huang Tatsuo Arai Key Laboratory of Biomimetic Robots and Sytems Ministry of EducationState Key Laboratory of Ielligent Control and Decision.of Complex SystemBeijing Advanced Innovation Center for Itelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBejing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 1828585Japan

Remotely controlled soft continuum robots with active steering capability have broad prospects in medical ***,conventional continuum robots have the miniaturization *** paper presents a microscale soft continuum microrobot with steering and locomotion capabilties based on magnetic field *** magnetically driven soft continuum microrobot is made of NdFeB particles and polyd imethylsiloxane(PDMS),and it can be as small as 200 pum in ***,a hydrogel layer is covered on the surface of the microrobot,which not only overcomes the adhesion force between the microobjects and the soft tip but also reduces the friction between the microrobot and *** performance test indicates the soft continuum microrobot featured excellent control and steering *** experimental results demonstrate that the soft continuum microrobot can travel through the microfluidic channel by its own vibration and flexibly steer in a bifurcation ***,the micromanipulation of microbeads in the microfluidic channels proves that the proposed microscale soft continuum microrobot has a great potential for intravascu lar manipu lation.

关键词： friction robot overcome

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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An Insulator Missing Defect Detection Method Based on Unmanned Aerial Vehicles

An Insulator Missing Defect Detection Method Based on Unmann...

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International Conference on control and Automation (ICCA)

作者： Yulong Zhang Zhongxian Zhou Lingxia Mu Xianghong Xue Jing Xin Youmin Zhang School of Automation and Information Engineering Xi'an University of Technology Xi'an Shaanxi China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, an insulator missing defect detection method is proposed based on unmanned aerial vehicles to solve the problem of glass insulator burst fault detection in high-voltage transmission lines. Firstly, the proposed method utilizes the improved Mask R-CNN (region-based convolutional neural network) algorithm to segment insulator strings in aerial images. Then, the constructed encoder-decoder network is used to extract and reconstruct features of the insulators, resulting in residual images. Finally, the residual images preserve the location information of the fault and obtains the result of missing insulators. The experiment shows that the proposed algorithm has high segmentation accuracy for insulators and high recognition accuracy for insulator missing faults.

关键词： Image segmentation Accuracy Power transmission lines Fault detection High-voltage techniques Insulators Feature extraction

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