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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Runmin Yang Rongni Yang Renjie Ma Yanzheng Zhu Peng Shi School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China School of Electrical and Mechanical Engineering University of Adelaide Adelaide SA Australia

ISBN: (数字)9798331528041

ISBN: (纸本)9798331528058

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

关键词： Sufficient conditions state feedback Two-dimensional displays Transforms Machine learning Stability analysis Data models Numerical models Closed loop systems Numerical stability

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Low-Cost Approach for Improving Video Transmission Efficiency in WVSN

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 600-605页

作者： LIU Min DENG Bin TANG Ying WU Minghu WANG Juan Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System.Hubei University of Technology Wuhan 430068.China Department of Electrical and Computer Engineering.Rowan University GlassboroNJ 08028USA State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Smart Education Qingdao Academy of Intelligent IndustriesQingdao 266041ShandongChina

The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring ***,there is still great challenge because of the limited wireless network *** resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image ***,an adaptively learning background model is improved to discover successive similar image frames from the inputting video ***,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element ***,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or *** evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to *** to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.

关键词： wireless visual sensor network(WVSN) temporal redundancy foreground background dynamic texture

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Realization of a Data-based Adaptive Networked Tracking control in NetCon System

Realization of a Data-based Adaptive Networked Tracking Cont...

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第40届中国控制会议

作者： Ye Zhao Shiwen Tong College of Urban Rail Transit and Logistics Beijing Union University College of Robotics Beijing Union University State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of Sciences

It is very difficult to realize the networked tracking control of a controlled process with unclear mechanism. An adaptive networked tracking control method that we proposed can solve such a problem. The method is a data-based control scheme started from the input-output data of the controlled process. We have realized it in the NetCon system. Firstly, the T-S fuzzy model of the controlled object is established according to input-output data by using fuzzy cluster modeling *** the fuzzy prediction model is obtained by transforming it into the fuzzy singleton model through equivalent transformation.A series of control actions are derived by inverting the fuzzy singleton model according to the reversibility condition. These predicted values can compensate the data dropout and time delay in the network communication channels. The influence of external disturbance and uncertainty on system performance is eliminated by using internal model structure and adaptive control method. Finally, experiment results in NetCon system show the effectiveness of the proposed method.

关键词： Fuzzy singleton model inverse model adaptive strategy NetCon system

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Reputation-based Distributed Filtering Over Sensor Networks Subject to Stochastic Nonlinearity and Network-Induced Quantization

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IEEE Transactions on Network Science and Engineering 2025年

作者： Jia, Chaoqing Wang, Zidong Hu, Jun Dong, Hongli Harbin University of Science and Technology School of Automation Harbin150080 China Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China Brunel University London Department of Computer Science UxbridgeUB8 3PH United Kingdom Harbin University of Science and Technology Department of Applied Mathematics Harbin150080 China Northeast Petroleum University Artificial Intelligence Energy Research Institute Daqing163318 China Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Daqing163318 China

In sensor networks, due to inevitable sensor faults, malfunctions, or deliberate attacks, sensors may transmit erroneous, inaccurate, or misleading data, thereby degrading overall system performance. To address this issue, an effective approach is to assign reputation scores to sensors based on their trustworthiness, historical performance, or reliability. In this paper, the reputation-based distributed filtering (RBDF) problem is considered for a class of stochastic nonlinear systems over sensor networks with network-induced quantization. A reputation mechanism is employed to mitigate the adverse effects caused by noisy, faulty, or malicious sensors. Specifically, reputations are allocated by each sensor to the data received from its neighbors, ensuring that abnormal data are assigned smaller reputation values and may even be discarded. For the first time, a recursive RBDF algorithm is proposed, wherein an upper bound of the filtering error covariance (UBFEC) is derived by solving two matrix equations. Subsequently, the filter gain is determined by minimizing the trace of UBFEC at each step. Furthermore, a sufficient condition is presented to ensure the uniform boundedness of the filtering error dynamics. Finally, a simulation example is provided to verify the feasibility and validity of the developed RBDF algorithm. © 2013 IEEE.

关键词： Digital arithmetic

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The 110kV Live-Maintaining Robot control System Design for Substation Equipment in complex Working Conditions 42

The 110kV Live-Maintaining Robot Control System Design for S...

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42nd Chinese control Conference, CCC 2023

作者： Hu, Chenyu Chen, Xin Li, Chengyu Huang, Guangxian Zhou, Cheng Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Future Technology China University of Geosciences Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Distribution Department Xianning437000 China State Grid Hubei Electric Power Co. Ltd Operations and Maintenance Department Xianning xian'An District Power Supply Company Xianning437000 China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Live-maintaining work is essential for continuous power supply to the substation. To improve the safety and efficiency of live-maintaining work, this paper proposes an equipotential live-maintaining robot system suitable for 110kV voltage levels. Considering the narrow space, complex working conditions and strong electromagnetic interference in substations, binocular vision technology, manipulator trajectory planning algorithm based on time-energy optimization, high voltage electromagnetic shielding technology are utilized to develop the system, and the live-maintaining robot is successfully applied in actual substation. By accurately identifying and locating the joint bolts and insulator, the robot system can achieve equipotential live-disassemble, live-assemble the joint bolts within 18 minutes and live-clean insulator within 5 minutes, demonstrating its the effectiveness and practicability. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Electromagnetic pulse

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Technical report:PID design of second-order non-linear uncertain systems with fractional order operations

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IET Cyber-systems and Robotics 2021年第4期3卷 343-346页

作者： Song Chen Tehuan Chen Chao Xu Jian Chu School of Mathematical Sciences Zhejiang UniversityHangzhouZhejiangChina School of Mechanical Engineering and Mechanics Ningbo UniversityNingboZhejiangChina Department of Automation Shanghai Jiao Tong UniversityShanghaiChina Ningbo Artificial Intelligence Institute Shanghai Jiao Tong UniversityNingboZhejiangChina The State Key Laboratory of Industrial Control Technology Institute of Cyber‐Systems and ControlZhejiang UniversityHangzhouZhejiangChina

This study considers a control problem related to the regulation of fractional-order systems controlled by fractional order proportional-integral-derivative controllers(PI^(λ)D^(μ)).The stability result of PIλDμ-based control systems is provided,such that the closed-loop systems can accomplish global stabilisation under some suitable conditions related to the system ***,a simulation is demonstrated to verify the results.

关键词： fractional operations verify

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A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking

arXiv

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arXiv 2021年

作者： Wang, Shuai Wei, Penghui Kong, Qingchao Mao, Wenji State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

To inhibit the spread of rumorous information and its severe consequences, traditional fact checking aims at retrieving relevant evidence to verify the veracity of a given claim. Fact checking methods typically use knowledge graphs (KGs) as external repositories and develop reasoning mechanism to retrieve evidence for verifying the triple claim. However, existing methods only focus on verifying a single claim. As real-world rumorous information is more complex and a textual statement is often composed of multiple clauses (i.e. represented as multiple claims instead of a single one), multi-claim fact checking is not only necessary but more important for practical applications. Although previous methods for verifying a single triple can be applied repeatedly to verify multiple triples one by one, they ignore the contextual information implied in a multi-claim statement and could not learn the rich semantic information in the statement as a whole. In this paper, we propose an end-to-end knowledge enhanced learning and verification method for multi-claim fact checking. Our method consists of two modules, KG-based learning enhancement and multi-claim semantic composition. To fully utilize the contextual information implied in multiple claims, the KG-based learning enhancement module learns the dynamic context-specific representations via selectively aggregating relevant attributes of entities. To capture the compositional semantics of multiple triples, the multi-claim semantic composition module constructs the graph structure to model claim-level interactions, and integrates global and salient local semantics with multi-head attention. We conduct experimental studies to validate our proposed method, and experimental results on a real-world dataset and two benchmark datasets show the effectiveness of our method for multi-claim fact checking over *** Codes 68T50 Copyright © 2021, The Authors. All rights reserved.

关键词： Knowledge graph

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Consistent and Asymptotically Efficient Localization from Range-Difference Measurements

arXiv

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arXiv 2023年

作者： Zeng, Guangyang Mu, Biqiang Shi, Ling Chen, Jiming Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen China The Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee the asymptotic identifiability of the model and show the consistency and asymptotic normality of the maximum likelihood (ML) estimator. Then, we devise an estimator that owns the same asymptotic property as the ML one. Specifically, we prove that the negative log-likelihood function converges to a function, which has a unique minimum and positive definite Hessian at the true source's position. Hence, it is promising to execute local iterations, e.g., the Gauss-Newton (GN) algorithm, following a consistent estimate. The main issue involved is obtaining a preliminary consistent estimate. To this aim, we construct a linear least-squares problem via algebraic operation and constraint relaxation and obtain a closed-form solution. We then focus on deriving and eliminating the bias of the linear least-squares estimator, which yields an asymptotically unbiased (thus consistent) estimate. Noting that the bias is a function of the noise variance, we further devise a consistent noise variance estimator that involves 3-order polynomial rooting. Based on the preliminary consistent location estimate, a one-step GN iteration suffices to achieve the same asymptotic property as the ML estimator. Simulation results demonstrate the superiority of our proposed algorithm in the large sample case. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Novel assisted cough system based on simulating cough airflow dynamics

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Bio-Design and Manufacturing 2021年第3期4卷 479-489页

作者： Shuai Ren Jinglong Niu Maolin Cai Liming Hao Yan Shi Weiqing Xu Zujin Luo School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China North Automatic Control Technology Institute Taiyuan 030006China Department of Respiratory and Critical Care Medicine Beijing Engineering Research Center of Respiratory and Critical Care MedicineBeijing Institute of Respiratory MedicineBeijing Chao-Yang HospitalCapital Medical UniversityBeijing 100043China

Cough is a defensive behavior that protects the respiratory system from infection and clears airway *** airflow dynamics have been analyzed by a variety of mathematical and experimental *** this paper,the cough airflow dynamics of 42 subjects were obtained and *** identification model based on piecewise Gauss function for cough airflow dynamics is proposed through the dimensionless method,which could achieve over 90%identification ***,an assisted cough system based on pneumatic flow servo system is *** vacuum situation and feedback control are used to increase the simulated peak cough flow rate,which are important for airway secretion clearance and to avoid airway collapse,*** simulated cough peak flow could reach 5 L/s without the external assistance such as manual pressing,patient cooperation and other ***,the backstepping control is developed to generate a simulated cough airflow that closely mimics the natural cough airflow of *** assisted cough system opens up wide opportunities of practical application in airway secretion clearance for critically ill patients with COVID 2019 and other pulmonary diseases.

关键词： Airflow dynamics Pneumatic system Simulated cough Model identification Airway secretion clearance

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∊-k anonymization and adversarial training of graph neural networks for privacy preservation in social networks

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Electronic Commerce Research and Applications 2021年 50卷 101105-101105页

作者： Tian, Hu Zheng, Xiaolong Zhang, Xingwei Zeng, Daniel Dajun The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

With the explosive growth of social networks, privacy preservation as a social good has been one common concern. Graph neural networks (GNNs) have been utilized by social network service providers to improve business service. However, traditional anonymization techniques of social networks cannot satisfy the desired privacy preservation of node attribute and graph structure and introduce information disturbance from the anonymization, leading to the performance degradation of GNNs in social network analysis. To protect sensitive user data and persist GNNs’ performance in social network analysis, we propose a two-stage privacy-preserving method of graph neural networks in the social network domain. During the first stage, we design a novel ∊-k anonymization method that can achieve ∊-local differential privacy (∊-LDP) and k-degree anonymity by incorporating the classical LDP and k-degree anonymization (k-DA) while retaining as much network community information as possible. At the second stage, we develop an adversarial training mechanism for GNNs to resist the disturbance from ∊-k anonymization and retain as much task performance as possible on anonymous social network data. Comprehensive experiments on several real-world social network datasets demonstrate the effectiveness of the proposed method for privacy-preserving node classification, link prediction, and graph clustering in social networks. The proposed method represents an interesting and important combination of classical anonymous technologies and recent GNNs and can preserve user privacy while providing business service. © 2021 Elsevier B.V.

关键词： Graph neural networks

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