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Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang Hongli Dong Yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical engineering and automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial intelligence Energy research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

关键词： filtering quadratic bounds

A Differential Privacy Federated Learning Scheme Based on Adaptive Gaussian Noise

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1679-1694页

作者： Sanxiu Jiao Lecai Cai Xinjie Wang Kui Cheng Xiang Gao College of automation and Information engineering Sichuan University of Science and EngineeringYibin644000China Sanjiang research Institute of Artificial intelligence and Robotics Yibin UniversityYibin644000China College of Mechanical engineering Sichuan University of Science and EngineeringYibin644000China

As a distributed machine learning method,federated learning(FL)has the advantage of naturally protecting data *** keeps data locally and trains local models through local data to protect the privacy of local *** federated learning method effectively solves the problem of artificial Smart data islands and privacy protection ***,existing research shows that attackersmay still steal user information by analyzing the parameters in the federated learning training process and the aggregation parameters on the server *** solve this problem,differential privacy(DP)techniques are widely used for privacy protection in federated ***,adding Gaussian noise perturbations to the data degrades the model learning *** address these issues,this paper proposes a differential privacy federated learning scheme based on adaptive Gaussian noise(DPFL-AGN).To protect the data privacy and security of the federated learning training process,adaptive Gaussian noise is specifically added in the training process to hide the real parameters uploaded by the *** addition,this paper proposes an adaptive noise reduction *** the convergence of the model,the Gaussian noise in the later stage of the federated learning training process is reduced *** paper conducts a series of simulation experiments on realMNIST and CIFAR-10 datasets,and the results show that the DPFL-AGN algorithmperforms better compared to the other algorithms.

关键词： Differential privacy federated learning deep learning data privacy

Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

Resilient control of flexible hypersonic vehicles against unmatched distributed faults

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Chinese Journal of Aeronautics 2024年第5期37卷 60-70页

作者： Dong ZHAO Wenjing REN School of Artificial intelligence Anhui UniversityHefei 230601China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China School of Electrical engineering and automation Hefei University of TechnologyHefei 230009China

This paper studies a robust fault compensation and vibration suppression problem of flexible hypersonic *** controlled plant is represented by a cascade system composed of a nonlinear Ordinary Differential Equation(ODE)and an Euler-Bernoulli Beam Equation(EBBE),in which the vibration dynamics is coupled with the rigid dynamics and suffers from distributed faults.A state differential transformation is introduced to transfer distributed faults to an EBBE boundary and a longitudinal dynamics is refined by utilizing T-S fuzzy IF-THEN rules.A novel T-S fuzzy based fault-tolerant control algorithm is developed and related stability conditions are *** robust exponential stability and well-posedness are proved by using the modified l_(0)-semigroup based Lyapunov direct approach.A simulation study on the longitudinal dynamics of flexible hypersonic vehicles effectively verifies the validity of the developed theoretical results.

关键词： Flexible hypersonic vehicles ODE-EBBE cascade Robust exponential stability Unmatched distributed fault compensation Vibration suppression

Virtual Coupling Trains Based on Multi-agent System Under Communication Delay

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Chinese Journal of Electronics 2024年

作者： Guodong QIN Xiangxi MENG Tao WEN Baigen CAI School of automation and intelligence Beijing Jiaotong University The Institute of System research China Industrial Control Systems Cyber Emergency Response Team

With the rapid development of railway transportation, virtual coupling(VC) has become a popular research topic. VC can greatly reduce tracking distance and increase the line capacity. Under VC control, the train formation control not only considers the behavior and speed adjustment strategy of the leader train but also the communication delays between trains. The quality of data communication between trains is an important aspect of train tracking control. We consider a virtually coupled train set(VCTS) as a multi-agent system. The Luenberger observer is introduced to estimate the real-time state of the train, based on the estimation, the train control consistency protocol is designed to account for communication delays. The stability of the error system is proven by constructing a Lyapunov function. The consistency of the coordinated train control is verified through simulation.

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of automation engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the engineering research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial intelligence Energy research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

Computational Experiments for Complex Social Systems:Integrated Design of Experiment System

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1175-1189页

作者： Xiao Xue Xiangning Yu Deyu Zhou Xiao Wang Chongke Bi Shufang Wang Fei-Yue Wang College of intelligence and Computing Tianjin UniversityTianjin 300350China School of Software Shandong UniversityJinan 250101China School of Artificial intelligence Anhui UniversityHefei 230601China School of Geographic and Environmental Sciences Tianjin Normal UniversityTianjin 300387China Institute of automation Chinese Academy of Sciences Beijing 100190China

Powered by advanced information industry and intelligent technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).And human factors have become crucial in the operations of complex social *** mechanical analysis and social simulations alone are powerless for analyzing complex social *** this backdrop,computational experiments have emerged as a new method for quantitative analysis of complex social systems by combining social simulation(e.g.,ABM),complexity science,and domain ***,in the process of applying computational experiments,the construction of experiment system not only considers a large number of artificial society models,but also involves a large amount of data and *** a result,how to integrate various data,model and knowledge to achieve a running experiment system has become a key *** paper proposes an integrated design framework of computational experiment system,which is composed of four parts:generation of digital subject,generation of digital object,design of operation engine,and construction of experiment ***,this paper outlines a typical case study of coal mine emergency management to verify the validity of the proposed framework.

关键词： artificial system operations

Positron Emission Tomography Lung Image Respiratory Motion Correcting with Equivariant Transformer

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Computers, Materials & Continua 2024年第5期79卷 3355-3372页

作者： Jianfeng He Haowei Ye Jie Ning Hui Zhou Bo She Faculty of Information engineering and automation Kunming University of Science and TechnologyYunnan Key Laboratory of Artificial IntelligenceKunming650500China School of Physics and Electronic engineering Yuxi Normal UniversityYuxi653100China PET/CT Center Affiliated Hospital of Kunming University of Science and TechnologyFirst People’s Hospital of Yunnan ProvinceKunming650031China

In addressing the challenge of motion artifacts in Positron Emission Tomography (PET) lung scans, our studyintroduces the Triple Equivariant Motion Transformer (TEMT), an innovative, unsupervised, deep-learningbasedframework for efficient respiratory motion correction in PET imaging. Unlike traditional techniques,which segment PET data into bins throughout a respiratory cycle and often face issues such as inefficiency andoveremphasis on certain artifacts, TEMT employs Convolutional Neural Networks (CNNs) for effective featureextraction and motion ***’s unique approach involves transforming motion sequences into Liegroup domains to highlight fundamental motion patterns, coupled with employing competitive weighting forprecise target deformation field generation. Our empirical evaluations confirm TEMT’s superior performancein handling diverse PET lung datasets compared to existing image registration networks. Experimental resultsdemonstrate that TEMT achieved Dice indices of 91.40%, 85.41%, 79.78%, and 72.16% on simulated geometricphantom data, lung voxel phantom data, cardiopulmonary voxel phantom data, and clinical data, respectively. Tofacilitate further research and practical application, the TEMT framework, along with its implementation detailsand part of the simulation data, is made publicly accessible at https://***/yehaowei/temt.

关键词： PET lung scans respiratory motion correction triple equivariant motion transformer lie group motion decomposition

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

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Computers, Materials & Continua 2024年第6期79卷 4149-4167页

作者： Yan Xiang Xuedong Zhao Junjun Guo Zhiliang Shi Enbang Chen Xiaobo Zhang Faculty of Information engineering and automation Kunming University of Science and TechnologyKunming650504China Yunnan Key Laboratory of Artificial intelligence Kunming University of Science and TechnologyKunming650500China Kunming Enersun Technology Co. Ltd.Kunming650217China

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information *** previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous ***,a unified CNER is often needed in real-world *** studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified ***,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved *** this study,we enhance the character-pair grid representation by incorporating both local and global ***,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation *** devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character *** approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition *** conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and *** results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

关键词： Chinese named entity recognition character-pair relation classification grid tagging U-shaped segmentation network