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Multisensor fusion estimation of nonlinear systems with intermittent observations and heavy-tailed noises

Science China(Information Sciences) 2022年第9期65卷 173-190页

作者： Bo XIAO Q.M.Jonathan WU Liping YAN School of Artificial Intelligence Beijing University of Posts and Telecommunications Department of Electrical and Computer Engineering University of Windsor Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Inspired by the robust student t-distribution based nonlinear filter(RSTNF), a student tdistribution and unscented transform(UT) based filter for state estimation of heavy-tailed nonlinear dynamic systems, a modified RSTNF for intermittent observations is derived. The fusion estimation for nonlinear multisensor systems with intermittent observations and heavy-tailed measurement and process noises is *** this work, the centralized fusion, the sequential fusion, and the na¨?ve distributed fusion algorithms are presented, respectively. Theoretical analysis shows that the presented algorithms are effective, which are the efficient extension of the classical unscented Kalman filter(UKF) or the cubature Kalman filter(CKF) based algorithms with Gaussian noises. Simulation results show that the presented algorithms are effective and feasible.

关键词： state fusion estimation nonlinear systems heavy-tailed noise intermittent observations multivariate $t$-distribution

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A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

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Computers, Materials & Continua 2023年第4期75卷 1157-1177页

作者： Guo-Wen Sun Gang Xiang Wei He Kai Tang Zi-Yi Wang Hai-Long Zhu School of Computer Science and Information Engineering Harbin Normal UniversitySongbei DistrictHarbin150025China Beihang University School of Automation Science and Electrical Engineering Beijing100191China Beijing Aerospace Automatic Control Institute Beijing100074China Rocket Force University of Engineering Xi’anShaanxi Province710025China

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

关键词： Self-adaptive quality factor belief rule base wireless sensor networks fault diagnosis

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Data-Based Soft Fault Diagnosis of a Three-Phase DC/AC Converter 7

Data-Based Soft Fault Diagnosis of a Three-Phase DC/AC Conve...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Chen, Cen Du, He Cai, Xi Wang, Haoran Zhai, Guofu Harbin Institute of Technology Department of Electrical Engineering and Automation Harbin China Engineering Corporation China Three Gorges Construction Chengdu China Three Gorges Intelligent Industrial Control Technology Company Wuhan China

ISBN: (纸本)9798350359558

With the widespread use of power electronic equipment, accurately identifying soft faults in power electronic converters is crucial for the stable and reliable operation of power electronic equipment. This paper proposed a soft fault diagnosis method for three-phase DC/AC converter using a data-based approach. Firstly, simulation analysis is conducted on the soft faults of three-phase DCI AC converter, and appropriate test signals are selected as data sources. Then, the LSTM neural network and its variants are used to obtain fault diagnosis models. Finally, the method is validated through experiments, and the results show that it has good performance in soft fault diagnosis of the three-phase DCI AC converter. © 2024 IEEE.

关键词： Failure analysis

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Optimization of Wide-Baseline Stereo Matching Based on Multi-view Geometry

Optimization of Wide-Baseline Stereo Matching Based on Multi...

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2024 China automation Congress, CAC 2024

作者： Xu, Yinhui Shan, Shuo Han, Gongben Fang, Shixiong Zhang, Kanjian Wei, Haikun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China Shenzhen Research Institute Southeast University Shenzhen China

ISBN: (纸本)9798350368604

Stereo vision plays a crucial role in scientific expeditions and facility maintenance. However, fixed-baseline stereo vision lacks accuracy for long-distance measurements, while wide-baseline stereo vision encounters occlusion issues at short distances. In this study, a wide-baseline stereo matching based on multi-view geometric constraints is proposed. Initially, the camera poses of multiple wide-baseline images are estimated, followed by image rectification and depth estimation. Subsequently, the disparity searching is constrained using geometric relationships among the views, resulting in more precise depth maps. Experiments were conducted to verify the superiority of the proposed method. The results indicate that the proposed method achieves an RMSE as low as 0.15 meters, even with invalid depth points. Compared to traditional stereo vision methods, accuracy is improved by approximately 35%, and robustness is significantly enhanced. In the aircraft runway scenario, overall depth map accuracy is higher, and occluded areas are significantly reduced. © 2024 IEEE.

关键词： Stereo vision

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Simulation of non-inductive vector control of permanent magnet synchronous motor based on sliding mode observer 3

Simulation of non-inductive vector control of permanent magn...

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3rd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Zhang, Caiyue Liu, Zipin Xu, Bowen Guilin University of Electronic Technology School of Electronic Engineering and Automation Guilin China Xi'An University of Science and Technology School of Electrical and Control Engineering Shaanxi Xi'an China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350398410

Permanent magnet synchronous motors (PMSM) are widely used due to their numerous benefits. It is critical to get rotor position and speed information in order to operate the motor accurately. Sensorless control techniques have emerged as a popular study area both at home and overseas. The sliding mode observer (SMO) may indirectly detect rotor position and has the benefits of easy implementation and efficient algorithms. In this study, a mathematical model for sensorless control of a PMSM is developed using SMO, vector control, and other techniques. With a surface-mounted PMSM as the study object, a mathematical model for sensorless control of PMSM is developed. PMSM's sliding mode observer model is built in the matlab/simulink environment. Experiments demonstrate that the system can track the rotor position and speed of the motor precisely and fulfill the requirements of sensorless vector control of PMSM. © 2023 IEEE.

关键词： Sensorless control

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Attention Markets of Blockchain-Based Decentralized Autonomous Organizations

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1370-1380页

作者： Juanjuan Li Rui Qin Sangtian Guan Wenwen Ding Fei Lin Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the negative effects of pro-posers’attention-capturing strategies that contribute to the“tragedy of the commons”and ensure an efficient distribution of attention among multiple proposals,it is necessary to establish a market-driven allocation scheme for DAOs’***,the Harberger tax-based attention markets are designed to facilitate its allocation via continuous and automated trading,where the individualized Harberger tax rate(HTR)determined by the pro-posers’reputation is ***,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as *** equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention ***,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is ***,the impact of individualized HTR on trading strategies is investigated,and results suggest that it has a negative correlation with leaders’self-accessed prices and ownership duration,but its effect on their revenues varies under different *** study is expected to provide valuable insights into leveraging attention resources to improve DAOs’governance and decision-making process.

关键词： Attention decentralized autonomous organizations Harberger tax Stackelberg game.

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Influences of Inhomogeneous Spatial Distribution of Global Oceanic Atmospheric Refractivity on LF Groundwave Propagation Delay

Influences of Inhomogeneous Spatial Distribution of Global O...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Wang, Dan-Dan Lu, Qi-Zirui Han, Chao Pu, Yu-Rong Yang, Rui-Hong Bai, Pei-Rui Shandong University of Science and Technology College of Electronic and Information Engineering Qingdao China Xi'an University of Technology Faculty of Automation and Information Engineering Xi'an China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350355581

Atmospheric refractivity affects the propagation delay of low-frequency (LF) groundwave in the realistic ocean environment. In this paper, a parabolic equation (PE) model based on the ERA5 meteorological reanalysis dataset is applied to analyze the influences of inhomogeneous spatial distribution of global oceanic atmospheric refractivity on LF groundwave propagation delay. The global oceanic atmospheric refractivity is derived from the meteorological quantities given by the ERA5 reanalysis dataset. It is found that the global oceanic surface atmospheric refractivity varies systematically with latitude in the range of 290∼300 N-unit to 380∼400 N-unit, which in turn leads to the variation of LF groundwave propagation delay reaching hundredth nanosecond for 1000 km-long propagation path. © 2024 IEEE.

关键词： global oceanic atmospheric refractivity low-frequency (LF) groundwave propagation parabolic equation (PE)

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A Review of Wind Turbine Blade Morphing:Power,Vibration,and Noise

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Fluid Dynamics & Materials Processing 2025年第4期21卷 657-695页

作者： Md.Mahbub Alam Center for Turbulence Control School of Mechanical Engineering and AutomationHarbin Institute of Technology(Shenzhen)Shenzhen518055China

Wind turbines play a vital role in renewable energy *** review examines advancements in wind turbine blade morphing technologies aimed at enhancing power coefficients,reducing vibrations,andminimizing noise ***,vibration,and noise levels can be optimized through morphing techniques applied to the blade’s shape,leading edge,trailing edge,and ***-edge morphing is particularly effective in improving efficiency and reducing noise,as flow attachment and separation at the leading edge significantly influence lift and vortex *** technologies often draw inspiration from bionic designs based on natural phenomena,highlighting the potential of biomimicry to improve aerodynamic performance and energy *** fluid-structure interactions is critical to ensuring the lifespan,performance,and safety of wind turbine blades,which directly affect operational efficiency and noise *** review underscores the importance of comprehending the interdependencies between aerodynamics,vibration,and noise to guide future research and policy in sustainable wind energy *** summarizing key advancements in the field,this paper serves as a valuable resource for researchers,policymakers,and industry leaders involved in wind energy technologies.

关键词： Wind turbine blade morphing efficiency vibration noise bionic renewable energy

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Reward Drops in Learning-based control with an Experimental Validation on Microdrones 63

Reward Drops in Learning-based Control with an Experimental ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Tukenmez, Nejat Fotiadis, Filippos Junior, Jose M. Magalhaes Vamvoudakis, Kyriakos G. Bogosyan, Seta O. Istanbul Technical University Mechatronics Engineering Department Istanbul34469 Turkey Georgia Institute of Technology School of Aerospace Engineering AtlantaGA United States Istanbul Technical University Control and Automation Engineering Department Istanbul34469 Turkey

ISBN: (纸本)9798350316339

In this paper, we consider a computationally efficient learning-based control mechanism dealing with dense reward processing for a zero-sum game. The problem has been formulated as the online learning of the Nash equilibrium without requiring any information on the system dynamics. It has firstly been constructed as an infinite horizon optimal control problem, then as an online model-free Q-learning framework, which is composed of critic and actor networks (i.e., for the control and disturbance input). The closed-loop system is also proved to have a stable equilibrium point even in the presence of reward drops. The efficacy of the learning-based controller has been validated through simulations and experiments on micro drones. © 2024 IEEE.

关键词： Contrastive Learning

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Impact Time Cooperative Guidance for Multi-Missile System Based on Incremental Learning 42

Impact Time Cooperative Guidance for Multi-Missile System Ba...

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42nd Chinese control Conference, CCC 2023

作者： Li, Xuheng Yu, Jianglong Dong, Xiwang Ren, Zhang Feng, Zhuo Liang, Biao School of Automation Science and Electrical Engineering Beihang University Science and Technology on Aircraft Control Laboratory Beijing100190 China Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789887581543

An impact time cooperative guidance method based on incremental learning is proposed for multi-missile cooperative guidance problem in the attack scenario. Firstly, a guidance model is established to represent the relationship of the missiles and the target. Secondly, an impact time coordinated guidance law based on the consensus method is designed. Then, time-to-go of the missile is predicted using an incremental learning algorithm, so that the accuracy of time-to-go can be better than the results calculated by traditional methods. Finally, the trained neural network is used to predict time-to-go. The results show that the algorithm can be used in the cooperative guidance law to complete the coordination in time, which is superior to the traditional guidance rate in coordination and has advantage in the scene of large maneuvering target. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Learning algorithms

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