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cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jing Yang Xingxia Wang Qinghua Ni Yuhang Liu Jing Wang Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350376739

ISBN: (纸本)9798350376746

In recent years, crowdsourcing systems that tackle complex tasks through the collective efforts of many individuals have garnered substantial attention. However, the existing crowd-sourcing systems face some challenges such as overreliance on human experience and effort, information overload, and risks of privacy breaches. To overcome these challenges, this paper proposes an intelligent and trustworthy crowdsourcing frame-work based on blockchain and retrieval-augmented generation. The framework centers around foundational models to integrate the three distinct and sequentially interdependent phases: task decomposition, task allocation or recommendation, and task execution, enabling the automatic provision of a personalized, comfortable, and efficient user experience. Blockchain and smart contracts are utilized to protect user privacy and interests without leaning on any third trusted authority. Additionally, the operational process of the framework is explained and validated by taking printed circuit board design and manufacturing as a case study and ChatGPT as its generator.

关键词： Crowdsourcing Retrieval augmented generation Smart contracts Privacy breach User experience Stability analysis Blockchains Social intelligence Resource management Reliability

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Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

引用

IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

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PiAGI: The Concept, Mechanism and Framework

PiAGI: The Concept, Mechanism and Framework

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Qiang Li Zhuoya Ju Lili Fan Xin Liu Wenhua Liu Feiyue Wang Scientific and Technological Innovation Center Beijing China The School of Automation Beijing Institute of Technology Beijing China School of Big Data & Cyber Security China University of Petroleum Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

As social production and living spaces gradually expand from the physical and information domains to the cognitive and social domains, this article addresses the new changes brought about by these expansions. Starting from the new impact of era of intelligent connectivity on social cognitive management, it analyzes the urgent need to enhance social cognitive management capabilities centered on cognitive decision-making, identifying the core key as Adversarial Generated Intelligence (AGI). It delves into the conceptual characteristics, operating mechanisms, and winning strategies of AGI, identifies the new challenges it faces, and proposes a Parallel Intelligence empowering AGI (PiAGI) system architecture through the empowerment of parallel intelligence. This provides theoretical support for improving social cognitive management capabilities centered on cognitive decision-making.

关键词： Decision making systems architecture Production Digital twins Faces

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Microstructure and Properties of a Novel High-Performance Al-Si-Mg Alloy Fabricated by Wire-Arc Directed Energy Deposition

SSRN

引用

SSRN 2023年

作者： Fang, Xuewei Li, Kai Ma, Minghua Shang, Jiahao Feng, Xuelei Hou, Yunhui Zhu, Ye Huang, Ke The State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an710054 China Xi’an Institute of Modern Control Technology Xi’an710065 China

In this study, a novel high-performance Al-Si-Mg alloy was fabricated using wire-arc directed energy deposition (wire-arc DED), resulting in remarkable mechanical properties,including a yield strength of 299.2 ± 1.3 MPa, an ultimate tensile strength of 376.5 ± 8.1 MPa and an elongation an elongation of 6.9 ± 0.3 %. The heat-treated samples exhibited a uniform distribution of a significant quantity of nanoscale ß'' phases, serving as the primary strengthening phase and contributing to substantial precipitation strengthening. The addition of Mn facilitates the formation of Al6(Mn, Fe) phase, effectively suppressed the formation of detrimental Fe-rich phases. However, the presence of numerous pores and the lack of fusion regions emerged as significant factors impacting mechanical properties. © 2023, The Authors. All rights reserved.

关键词： Microstructure

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Differentially Private Recursive Least Squares Estimation for ARX systems with Multi-Participants

arXiv

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arXiv 2025年

作者： Tan, Jianwei Wang, Jimin Zhang, Ji-Feng Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China School of Automation and Electrical Engineering Zhongyuan University of Technology Zheng Zhou450007 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

This paper proposes a differentially private recursive least squares algorithm to estimate the parameter of autoregressive systems with exogenous inputs and multi-participants (MP-ARX systems) and protect each participant’s sensitive information from potential attackers. We first give a rigorous differential privacy analysis of the algorithm, and establish the quantitative relationship between the added noises and the privacy-preserving level when the system is asymptotically stable. The asymptotic stability of the system is necessary for ensuring the differential privacy of the algorithm. We then give an estimation error analysis of the algorithm under the general and possible weakest excitation condition without requiring the boundedness, independence and stationarity on the regression vectors. Particularly, when there is no regression term in the system output and the differential privacy only on the system output is considered, Ε-differential privacy and almost sure convergence of the algorithm can be established simultaneously. To minimize the estimation error of the algorithm with Ε-differential privacy, the existence of the noise intensity is proved. Finally, two examples are given to show the efficiency of the algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Differential privacy

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Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1990-2004页

作者： Linyao Yang Chen Lv Xiao Wang Ji Qiao Weiping Ding Jun Zhang Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the China Electric Power Research Institute Beijing 100192China IEEE the Qingdao Academy of Intelligent Industries Qingdao 256200China the School of Information Science and Technology Nantong UniversityNantong 226019China the School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based *** recent years,researchers in the field of power systems have explored KGs to develop intelligent dispatching systems for increasingly large power *** multiple power grid dispatching knowledge graphs(PDKGs)constructed by different agencies,the knowledge fusion of different PDKGs is useful for providing more accurate decision *** achieve this,entity alignment that aims at connecting different KGs by identifying equivalent entities is a critical *** entity alignment methods cannot integrate useful structural,attribute,and relational information while calculating entities’similarities and are prone to making many-to-one alignments,thus can hardly achieve the best *** address these issues,this paper proposes a collective entity alignment model that integrates three kinds of available information and makes collective counterpart *** model proposes a novel knowledge graph attention network(KGAT)to learn the embeddings of entities and relations explicitly and calculates entities’similarities by adaptively incorporating the structural,attribute,and relational ***,we formulate the counterpart assignment task as an integer programming(IP)problem to obtain one-to-one *** not only conduct experiments on a pair of PDKGs but also evaluate o ur model on three commonly used cross-lingual *** comparisons indicate that our model outperforms other methods and provides an effective tool for the knowledge fusion of PDKGs.

关键词： Entity alignment integer programming(IP) knowledge fusion knowledge graph embedding power dispatch

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Data-Driven Model for Detection,Isolation and Accommodation of Faulty Angle of Attack Sensor Measurements in Fixed Winged Aircraft

Data-Driven Model for Detection,Isolation and Accommodation ...

引用

第34届中国控制与决策会议

作者： Bemnet Wondimagegnehu Mersha Hongbin Ma School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

Ethiopian Airlines' Boeing 737-8 MAX nosedived and crashed shortly after takeoff on March 10,2019,at Ejere Town,south of Addis Ababa.A faulty angle of attack(AOA) sensor was the cause of the *** airplane accidents have been linked to faulty AOA sensors in the *** majority of the AOA sensor fault detection,isolation,and accommodation(SFDIA) literature relied on linear model-driven techniques,which are not suitable when the system's model is uncertain,complex,or *** multilayer perceptron(MLP) models have been employed in datadriven models in the literature and the effectiveness of deep learning-based data-driven models has not been *** this work,a data collection and processing method that ensures the collected data is not monotonous and a data-driven model for AOA SFDIA is *** proposed model uses a deep learning-based recurrent neural network(RNN) to accommodate for faulty AOA measurement under flight conditions with faulty AOA measurement,faulty total velocity measurement,and faulty pitch rate *** residual analysis with a fixed threshold is used to detect and isolate faulty AOA *** proposed and benchmark models are trained with the adaptive momentum estimation(Adam) *** show that the proposed model effectively detects,isolates,and accommodates faulty AOA measurements when compared to other data-driven benchmark *** method is able to detect and isolate faulty AOA sensors with a detection delay of 0.5 seconds for ramp failure and 0.1 seconds for step failure.

关键词： Data-driven modeling Intelligent transportation systems Faulty angle of attack measurement Sensor fault Detection Isolation and Accommodation(SFDIA) and Recurrent neural network

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Relative Localization for UAV-UGV Based on Correlation of Bearing and Distance

Relative Localization for UAV-UGV Based on Correlation of Be...

引用

IEEE International Conference on Mechatronics and Automation

作者： Jia Guo Kang Hu Jinting Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough.

关键词：

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Coordinated Motion control for a Six-wheel-drive Skid-steering Mobile Robot

Coordinated Motion Control for a Six-wheel-drive Skid-steeri...

引用

2021 China Automation Congress, CAC 2021

作者： Xu, Yongkang Wang, Shoukun Zhao, Hongqiang Chen, Zhihua State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China State Key Laboratory of High Performance and Complex Manufacturing Central South University Changsha China

ISBN: (纸本)9781665426473

A speed consensus control strategy for a six-wheel-drive skid-steering mobile robot was proposed based on a hierarchical controller in a complex environment with unknown disturbances. The effective method of reliable speed consensus control strategy should consider some disturbances, such as the internal-robot assembly error, which including instability of motor control system and external physical interference in robot dynamic system. In this paper, a driving anti-slip control system with PID and the stability control system with sliding mode by variable structure is designed and integrated to elevate the stability of the robot. And, a G-vector control algorithm based on sliding mode control is proposed to reduce the yaw angle as much as possible during the process of differential steering of robots. The effectiveness of the proposed control strategy is verified by an example of a *** results show that the method has good control performance in control accuracy and stability. © 2021 IEEE

关键词： Motion control

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Ground maneuver for front-wheel drive aircraft via deep reinforcement learning

引用

Chinese Journal of Aeronautics 2021年第10期34卷 166-176页

作者： Hao ZHANG Zongxia JIAO Yaoxing SHANG Xiaochao LIU Pengyuan QI Shuai WU School of Automation Science and Electrical Engineering Bcihcmg UniversityBeijing 100083China Research Institute for Frontier Science Beihang UniversityBeijing 1000H3China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Key Laboratory of Advanced Aircraft Systems(Beihang University) Ministry of Industry and Information TechnologyBeijing 100083China Ningbo Institute of Technology Beihang UniversityNingbo 315800China The State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University.Hangzhou 310027China

The maneuvering time on the ground accounts for 10%–30%of their flight time,and it always exceeds 50%for short-haul aircraft when the ground traffic is *** also contribute significantly to emissions,fuel burn,and noise when taxiing on the ground at *** is an urgent need to reduce aircraft taxiing time on the ***,it is too expensive for airports and aircraft carriers to build and maintain more runways,and it is space-limited to tow the aircraft fast using *** drive capability is currently the best solution for aircraft,which can save the maneuver time for *** idea is proposed that the wheels are driven by APU-powered(auxiliary power unit)motors,APU is working on its efficient point;consequently,the emissions,fuel burn,and noise will be reduced *** Front-wheel drive aircraft,the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a *** traction effects the aircraft’s maximum turning ability,which is difficult to be modeled to guide the controller *** reinforcement learning provides a powerful tool to help us design controllers for black-box models;however,the models of related works are always simplified,fixed,or not easily modified,but that is what we care about *** with complex models can the trained controller be ***-fidelity models that can easily modified are necessary for aircraft ground maneuver controller *** paper focuses on the maneuvering problem of front-wheel drive aircraft,a high-fidelity aircraft taxiing dynamic model is established,including the 6-DOF airframe,landing gears,and nonlinear tire force model.A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive *** is proved that in some conditions,the DRL based controller outperformed conventional look-ahead controllers.

关键词： Front-wheel drive aircraft Ground maneuver Nose wheel steering Tire model Magic equation Deep reinforcement learning

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