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Decentralized fault diagnosis of discrete-event systems with unreliable sensors using linear temporal logic

Science China(Information Sciences) 2025年第1期68卷 322-341页

作者： Weijie DONG Shaoyuan LI Xiang YIN Key Laboratory of System Control and Information Processing Ministry of EducationDepartment of Automation Shanghai Jiao Tong University

In this paper,we investigate a decentralized diagnosis problem of a discrete-evnt system(DES) subject to unreliable sensors,where the sensor observations of local diagnosers may be non-deterministic as a result of possible *** studies on decentralized robust diagnosis can only deal with different types of sensor failures separately,e.g.,all sensors suffer from the same type of sensor failures such as intermittent sensor failures or permanent sensor ***,since sensors of different local diagnosers may face different external environments and have different internal characteristics,sensors corresponding to different local diagnosers may also have their own fault *** this paper,we propose a flexible framework of decentralized diagnosis for DES subject to unreliable sensors such that sensors of different local diagnosers are permitted to have different types of sensor *** this end,we extend the existing decentralized diagnosis framework to the case where there exist common sensors broadcasting their observations to all local *** apply linear temporal logic(LTL) to constrain infinite behaviors of private sensors of local diagnosers and common ***,a new notion of φ-codiagnosability is proposed as the necessary and sufficient condition for the existence of a decentralized diagnoser that works correctly under sensors,satisfying LTL-based sensor ***,we provide an effective approach to verify the φ-codiagnosability.

关键词： discrete event systems decentralized diagnosis codiagnosability automata

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Short-Term Residential Load Forecasting via Pooling-Ensemble Model with Smoothing Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3690-3702页

作者： Xiao, Jiang-Wen Fang, Hongliang Wang, Yan-Wu Huazhong University of Science and Technology Ministry of Education School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China

Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal with these problems, this article proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole short-term load forecasting framework in this article contains three steps. Specifically and first, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Second, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Third, multiple predictors in the pooling-ensemble model are selected for different states and the load is forecasted by weighing the results of the multiple predictors based on the predicted states. Results of the case studies and comparison studies on two public datasets verify the advantages of the smoothing clustering method and the pooling-ensemble model. © 2020 IEEE.

关键词： Probability distributions

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Value Iteration-Based Distributed Adaptive Dynamic Programming for Multi-Player Differential Game With Incomplete Information

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 436-447页

作者： Yun Zhang Yuqi Wang Yunze Cai the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China the National Key Laboratory of Air-based Information Perception and Fusion

In this paper, a distributed adaptive dynamic programming(ADP) framework based on value iteration is proposed for multi-player differential games. In the game setting,players have no access to the information of others' system parameters or control laws. Each player adopts an on-policy value iteration algorithm as the basic learning framework. To deal with the incomplete information structure, players collect a period of system trajectory data to compensate for the lack of information. The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy. Theoretical analysis shows that by adopting proximal policy searching rules, the approximated policies can converge to a neighborhood of equilibrium policies. The efficacy of our method is illustrated by three examples, which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.

关键词： Distributed adaptive dynamic programming incomplete information multi-player differential game (MPDG) value iteration

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Value Iteration-Based Cooperative Adaptive Optimal control for Multi-Player Differential Games With Incomplete Information

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 690-697页

作者： Yun Zhang Lulu Zhang Yunze Cai the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence *** players are divided into two groups in the learning process and adapt their policies *** method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based ***,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control *** efficacy of our method is illustrated by three examples.

关键词： Adaptive dynamic programming incomplete information multi-player differential game value iteration

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Applications of artificial intelligence to lipid nanoparticle delivery

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Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

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Distributed robust iterative learning control for AC microgrids with external disturbances

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Science China(Information Sciences) 2025年

作者： Hongyu SU Jingang LAI School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlMinistry of Education Huazhong University of Science and Technology

This study proposes a distributed secondary control scheme based on distributed robust iterative learning control(DRILC) for islanded alternating current(AC) microgrids subjected to external disturbances. By employing the decoupled sliding mode consensus approach, voltage regulation, frequency restoration, and accurate active power sharing can be achieved within a finite time on the proposed novel integral terminal sliding mode(ITSM) manifold. Furthermore, the appropriate iterative update law in the ITSM-based controller is utilized to learn and eliminate external disturbances as effectively as possible. In the proposed control scheme, the iterative learning control and sliding mode control are designed to function in a complementary manner, which enhances the performance of the secondary control scheme for multi-objective regulations. The stability criteria and robustness to external disturbances of the closed-loop microgrid system in the iteration and time domains are also rigorously derived with the help of the Lyapunov direct method. Finally, the effectiveness of the proposed secondary control scheme is validated by case studies of an islanded AC microgrid test system in the MATLAB/SimPowerSystems software environment.

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Real-time tracking of fast-moving object in occlusion scene

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Journal of Systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Systems Control and Information Processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Investigation of conformational changes of cathepsin B as a feasibility assessment for NaCl reduction in Jinhua ham

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Food Science and Human Wellness 2025年第2期14卷 429-438页

作者： Shiqi Hu Guanghong Zhou Xinglian Xu Wangang Zhang Chunbao Li Key Laboratory of Meat Processing and Quality Control Ministry of EducationKey Laboratory of Meat ProcessingMinistry of Agriculture and Rural AffairsJiangsu Synergetic Innovation Center of Meat Processing and Quality ControlCollege of Food Science and TechnologyNanjing Agricultural UniversityNanjing 210095China School of Life Science and Food Engineering Huaiyin Institute of TechnologyHuai’an 223003China

To regulate the sodium chloride content in Jinhua ham,the impact of NaCl on the activity and conformation of cathepsin B was investigated using spectroscopy and computational *** results showed that the activity of cathepsin B decreased with an increase in Na^(+)cation content and ***,decreasedα-helix content and increasedβ-sheet content were *** increase in sulfhydryl group content was attributed to the breaking of original disulfide bonds in the molecular structure or the release of embedded ***,the surface hydrophobicity gradually declined,which was consistent with the analysis of endogenous fluorescence *** the molecular level,the number of hydrogen bonds formed in NaCl-treated samples decreased,and the interactions between the hydrogen bonding were less powerful,which caused instability in the binding of the protein and *** conformation of cathepsin B accurately characterized its activity,and the structural changes had a macroscopic effect on the decrease in protease activity.

关键词： Protein conformation Cathepsin B activity Jinhua ham Molecular docking Molecular dynamics

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controllability of neighborhood Corona product networks

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Science China(Information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5350-5367页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Layout Three-dimensional displays image reconstruction Estimation Cameras Floors Cognition Transforms Training Semantics

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