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

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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

A Cross-Multi-Domain Trust Assessment Authority Delegation Method Based on Automotive Industry Chain

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Computers, Materials & Continua 2025年第1期82卷 407-426页

作者： Binyong Li Liangming Deng Jie Zhang Xianhui Deng School of Cybersecurity(Xin Gu Industrial College) Chengdu University of Information TechnologyChengdu610225China Advanced Cryptography and system Security Key Laboratory of Sichuan Province Chengdu610225China SUGON Industrial control and Security Center Chengdu610225China

To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply relationships in the automotive market,improving data sharing and interactions across various platforms,and achieving more detailed integration of data and *** propose a trust evaluation permission delegation method based on the automotive industry *** proposed method combines smart contracts with trust evaluation mechanisms,dynamically calculating the trust value of users based on the historical behavior of the delegated entity,network environment,and other factors to avoid malicious node attacks during the permission delegation *** also introduce strict control over the cross-domain permission granting and revocation mechanisms to manage the delegation path,prevent information leakage caused by malicious node interception,and effectively protect data integrity and *** analysis shows that this method meets the realtime requirements of collaborative interaction in the automotive industry chain and provides a feasible solution to permission delegation issues in the automotive industry chain,offering dynamic flexibility in authorization and scalability compared to most existing solutions.

关键词： Automotive industry chain cross-domain access block chain delegate authority trust assessment

Embedding prescribed-time adaptive control protocol unveiling distributed consensus in multirobot systems via directed topology

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Science China(Information Sciences) 2025年

作者： Yonghao XIE Xinru MA Hengyu LI Shaorong XIE School of Computer Engineering and Science Shanghai University School of mechatronic Engineering and Automation Shanghai University

Recently, multirobot systems （MRSs） have found extensive applications across various domains, including industrial manufacturing, collaborative formation of unmanned equipment, emergency disaster relief, and war scenarios[1]. These advancements are largely supported by the development of consistency control theory. However, traditional dynamicsfree models may cause instability in complex robotic systems. Lagrangian dynamics offers a better approach for modeling these systems, as it facilitates controller design and optimization analysis. Despite this, challenges persist with unknown parameters and nonlinear friction within the systems.

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New method of improving the security of the hyperchaotic cryptosystem

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Journal of systems Engineering and Electronics 2005年第3期16卷 515-520页

作者：谢鲲雷敏冯正进 Inst .of mechatronic control system Shanghai Jiaotong Univ

In chaotic cryptosysterns, using （very） high dimensional chaotic attractors for encrypting a given message maybe can improve the privacy of chaotic encoding. A kind of hyperchaotic systems are studied by using some classical methods. The results show that for improving the security of the chaotic cryptosystems, besides the high dimension, the sub-Nyquist sampling interval （SI） is also necessary. Then, we verify this result using the methods of time series analysis.

关键词： hyperchaotic cryptosystem time series analysis Volterra-Wiener-Korengerg test surrogate data.

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Dynamic event-triggered data-driven iterative learning bipartite tracking control for nonlinear MASs with prescribed performance

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Science China(Information Sciences) 2025年第1期68卷 292-305页

作者： Tao SHI Wei-Wei CHE School of mechatronic Engineering and Automation Shanghai University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University College of Information Science and Engineering Northeastern University

This article proposes a distributed dynamic event-triggered data-driven iterative learning control(DET-DDILC)scheme under a predefined performance to tackle the bipartite tracking control problem for multiagent systems(MASs). An improved dynamic linearization technique is utilized to convert the nonlinear MASs into an iterative linear data model. First,a peer-to-peer mapping function is introduced to map the constrained distributed system output homeomorphism to an unconstrained one. In addition, a DET mechanism based on a time-iteration-varying function is devised to conserve network communication resources. Based on the unconstrained transformation and the designed DET mechanism, the DET-DDILC algorithm is devised to ensure that the bipartite tracking performance of MASs can be within the preset range. Finally, the effectiveness and feasibility of the designed control scheme are demonstrated via a simulation case by a comparison.

关键词： bipartite tracking control prescribed performance event-triggered iterative learning control multiagent systems

An Artificial Intelligence‑Assisted Flexible and Wearable Mechanoluminescent Strain Sensor system

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Nano-Micro Letters 2025年第3期17卷 217-231页

作者： Yan Dong Wenzheng An Zihu Wang Dongzhi Zhang College of control Science and Engineering China University of Petroleum(East China)Qingdao 266580People’s Republic of China

The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable *** tackle these challenges,this work develops an artificial intelligenceassisted,wireless,flexible,and wearable mechanoluminescent strain sensor system(AIFWMLS)by integration of deep learning neural network-based color data processing system(CDPS)with a sandwich-structured flexible mechanoluminescent sensor(SFLC)*** SFLC film shows remarkable and robust mechanoluminescent performance with a simple structure for easy *** CDPS system can rapidly and accurately extract and interpret the color of the SFLC film to strain values with auto-correction of errors caused by the varying color temperature,which significantly improves the accuracy of the predicted strain.A smart glove mechanoluminescent sensor system demonstrates the great potential of the AIFWMLS system in human gesture ***,the versatile SFLC film can also serve as a encryption *** integration of deep learning neural network-based artificial intelligence and SFLC film provides a promising strategy to break the“color to strain value”bottleneck that hinders the practical application of flexible colorimetric strain sensors,which could promote the development of wearable and flexible strain sensors from laboratory research to consumer markets.

关键词： Mechanoluminescent Strain sensor Flexible Deep learning Wireless

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Day-ahead Electricity Price Prediction Method Based on Similar Day Screening and Combined Deep Learning Modeling

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Dianwang Jishu/Power system Technology 2025年第1期49卷 242-251页

作者： Ai, Yu Jia, Yanbing Han, Xiaoqing Shanxi Key Laboratory of Power system Operation and control Taiyuan University of Technology Shanxi Province Taiyuan 030024 China Key Laboratory of Cleaner Intelligent control on Coal & Electricity Taiyuan University of Technology Ministry of Education Shanxi Province Taiyuan 030024 China

Accurate day-ahead electricity price prediction is the basis for market operation and policy planning, while market disclosure information is essential for electricity price prediction. This paper proposes a combined CNN-GRU deep-learning electricity price prediction model introducing the Self-attention mechanism. Firstly, for the trading process of the Shanxi electricity spot market and the formation mechanism of electricity price before the day, it is proposed to adopt the maximum mutual information coefficient method to extract features from the market disclosed information data such as boundary conditions before the day, to determine the key influencing factors of electricity price and its weight coefficients;and then based on the weighted grey correlation of the history of similar day screening method to generate the historical dataset of electricity price prediction, and to excavate the internal change rule of electricity price and its features;Finally, the CNN-GRU model introducing Self-attention mechanism is used to get the predicted electricity price based on the historical data set. The effectiveness and accuracy of the prediction method proposed in this paper are verified through examples. © 2025 Power system Technology Press. All rights reserved.

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A Review on Thermal Management of Li-ion Battery:from Small-Scale Battery Module to Large-Scale Electrochemical Energy Storage Power Station

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Journal of Thermal Science 2025年第1期34卷 1-23页

作者： CHEN Zhifeng JIA Li YIN Liaofei DANG Chao REN Honglei ZHANG Zhiqiang Beijing Key Laboratory of Flow and Heat Transfer of Phase Changing in Micro and Small Scale School of MechanicalElectronic and Control EngineeringBeijing Jiaotong University

Li-ion battery is an essential component and energy storage unit for the evolution of electric vehicles and energy storage technology in the ***,in order to cope with the temperature sensitivity of Li-ion battery and maintain Li-ion battery safe operation,it is of great necessary to adopt an appropriate battery thermal management system(BTMS).In this paper,the current main BTM strategies and research hotspots were discussed from two aspects:small-scale battery module and large-scale electrochemical energy storage power station(EESPS).The practical application situation,advantages and disadvantages,and the future development trend of each heat dissipation method(air,liquid,PCM,heat pipe,hybrid cooling) were described in *** them,the air cooling and liquid cooling were reviewed in-depth based on the engineering *** PCM,heat pipe and hybrid cooling were reviewed extensively based on the latest *** research provides a comprehensive understanding for the BTMS in all scales.

关键词： battery thermal management cooling methods large-scale electrochemical energy storage power station small-scale battery module

Contact Model of Revolute Joint with Clearance Based on Fractal Theory

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Chinese Journal of Mechanical Engineering 2018年第6期31卷 34-44页

作者： Shi-Hua Li Xue-Yan Han Jun-Qi Wang Jing Sun Fu-Juan Li Parallel Robot and mechatronic system Laboratory of Hebei Province Yanshan University

The contact sti ness of a mechanical bonding surface is an important parameter in determining the normal and radial contact force. To improve the calculation accuracy of the contact force model, the surface roughness of the bonding surface and the energy loss that necessarily occurs during the impact process should be considered com?prehensively. To study the normal contact force of a revolute joint with clearance more accurately in the case of dry friction, a nonlinear sti ness coe cient model considering the surface roughness was established based on fractal theory, which considers the elastic, elastic?plastic, and plastic deformations of the asperities of the contact surface during the contact process. On this basis, a modified nonlinear spring damping model was established based on the Lankarani–Nikravesh contact force model. The laws influencing the surface roughness, recovery coe cient, initial velocity, and clearance size on the impact force were revealed, and were compared with the Lankarani–Nikravesh model and a hybrid model using MATLAB. The maximum impact force was obtained using a modified contact force model under di erent initial velocities, di erent clearances, and di erent degrees of surface roughness, and the calculated results were then compared with the experiment results. This study indicates that the modified model can be used more widely than other models, and is suitable for both large and small clearances. In particular, the modified model is more accurate when calculating the contact force of a revolute joint with a small clearance.

关键词： Fractal theory Modified contact model Surface roughness Lankarani–Nikravesh model

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