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Prognostics and system Health Management Conference (PHM)

作者： Guoyan Li Jingbin Zhang Guoliang Lu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Advance Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan China Key Laboratory of High-efficiency and Clean Mechanical Manufacture of MOE National Demonstration Center for Experimental Mechanical Engineering Education School of Mechanical Engineering Shandong University Jinan China

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Capsule network is an innovative deep learning-based model that uses neuron vectors as inputs and outputs of the network. It can achieve independent output of multiple classification labels, and solve the problem of decoupling recognition of compound fault components in planetary gearboxes. However, the single-scale feature extraction cannot fully explore multi-scale feature information in compound fault signals. This study proposes a capsule network combined with multi-scale convolutional feature fusion to diagnose the compound fault of planetary gearbox. The multi-scale features are extracted from STFT images of vibration signals using convolutional layers with different kernel sizes; secondly, a capsule network is designed to classify and identify the fault components by using the dynamic routing algorithm. The experiments are conducted to assess the performance of the proposed method, and the results indicates that it can effectively decoupling identify the compound faults with strong anti-interference and stability.

关键词： Fault diagnosis Vibrations Convolution Heuristic algorithms Feature extraction Stability analysis Vectors

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Predicting influenza-like illness trends based on sentinel surveillance data in China from 2011 to 2019:A modelling and comparative study

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Infectious Disease Modelling 2024年第3期9卷 816-827页

作者： Xingxing Zhang Liuyang Yang Teng Chen Qing Wang Jin Yang Ting Zhang Jiao Yang Hongqing Zhao Shengjie Lai Luzhao Feng Weizhong Yang School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing100073China State Key Laboratory of Respiratory Health and Multimorbidity China Key Laboratory of Pathogen Infection Prevention and Control(Peking Union Medical College) Ministry of EducationChina National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionChina Department of Management Science and Information System Faculty of Management and EconomicsKunming University of Science and TechnologyKunming650506China Department of Applied Mathematics&Statistics Stony Brook UniversityStony BrookNY11794-3600USA WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonSO171BJUK

Background Influenza is an acute respiratory infectious disease with a significant global disease ***,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of ***,comparative studies on the performance of innovative models and approaches used for influenza prediction are ***,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive *** The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in China,based on sentinel surveillance data from 2011 to *** relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three *** Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in ***,the models’predictive performance declined as the weeks ahead ***,blocked cross-validation indicated that all models were robust to changes in data and had low risks of *** Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid ***,in the future,the ARMA—GARCH model may be used

关键词： Influenza-like illness Influenza Sentinel surveillance China Predicting Modeling

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Predefined Performance Tracking control Design for a VTOL Aircraft system

Predefined Performance Tracking Control Design for a VTOL Ai...

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Robotics, intelligent control and Artificial Intelligence (RICAI), International Conference on

作者： Xiongfeng Deng Binzi Xu Liang Tao Key Laboratory of Electric Drive and Control of Anhui Higher Education Institutes Anhui Polytechnic University Wuhu China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Anhui Polytechnic University Wuhu China

This work discusses the predefined performance tracking control issue of a vertical take-off and landing (VTOL) aircraft system. By using the designed control performance function, the constrained error signal of the aircraft system can be switched into an equivalent unconstrained signal. Moreover, fuzzy logic systems are introduced to cope with the aircraft system's unknown nonlinear dynamics. And then, adaptive fuzzy sliding control laws are designed by combining the fuzzy control method with the sliding mode control technique. Based on the designed control law, it is not only ensured that the outputs of the VTOL aircraft system can track the desired trajectories, but also that the tracking errors are constrained within a predefined range. Finally, the availability of proposed control method is testified through simulation example.

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An Optimal Scheduling Strategy for Wind-PV and Multi-Type Energy Storage Co-Generation system

An Optimal Scheduling Strategy for Wind-PV and Multi-Type En...

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IEEE International Conference on Power and Energy Applications (ICPEA)

作者： Huan Ma Hao Tian Kunpeng Zhang Yutian Liu Shandong Electric Power Research Institute Jinan China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

Multi-type energy storage is essential for managing fluctuations in renewable energy power and increasing the consumption rate of renewable energy. In this paper, an optimal scheduling strategy for the co-generation system comprising wind power, photovoltaic power, electrical energy storage, and hydrogen energy storage is proposed. The strategy consists of a global optimization model and an application-oriented Pareto optimal solution screening methodology. The global optimization model establishes a multi-objective optimization model based on meteorological prediction information that considers the intended output power completion of the co-generation system, the remaining equivalent power of the energy storage plant, and the equivalent production of hydrogen. The NSGA-II is utilized to solve the global optimization model and obtains multiple Pareto optimal solutions. The optimal solutions are screened by applying the application-oriented Pareto optimal solution screening methodology. Finally, a co-generation plant in Shandong Province is presented to validate the effectiveness of the proposed approach in mitigating wind variability and encouraging the adoption of renewable energy sources.

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Distributed Optimization of Heterogeneous Linear Multi-Agent systems with Unknown Disturbances

Distributed Optimization of Heterogeneous Linear Multi-Agent...

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IEEE Conference on Decision and control

作者： Mengmeng Duan Shanying Zhu Ziwen Yang Cailian Chen Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we investigate the distributed optimization problem for heterogeneous linear multi-agent systems with unknown disturbances. By applying the primal-dual method and the time-scale separation technique, a distributed dynamic controller without using any disturbance information is proposed. Based on the optimal condition, the relationship between the optimal solution and the equilibrium point of the system is established, and it is shown that the distributed optimization problem is solved provided that the closed-loop system is stable. Then, inspired by the nonsingular perturbation analysis, it is proved that the closed-loop system is exponentially input-to-state stable with respect to the derivative of the disturbance. Numerical examples are provided to illustrate the theoretical results.

关键词： Perturbation methods Trajectory Closed loop systems Optimization Multi-agent systems

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Wireless/wired integrated transmission for industrial cyber-physical systems: risk-sensitive co-design of 5G and TSN protocols

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Science China(Information Sciences) 2022年第1期65卷 56-71页

作者： Yajing ZHANG Qimin XU Xinping GUAN Cailian CHEN Mingyan LI Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management College of Computer Science Chongqing University

The growing popularity of intelligent manufacturing is driven by deterministic transmission demands of applications in industrial cyber-physical systems(ICPS). However, the ossified shortages of industrial wireless communication such as diverse quality of service(Qo S) and complex signaling processes incur a severe long tail of transmission delay distribution. As a solution, the 5 th generation(5 G) wireless communication technology provides ultra-reliable and low-latency communication(URLLC) for industry scenarios. Moreover, the newly proposed time-sensitive networking(TSN) standards guarantee the transmission determinacy by gate mechanism. In this paper, we propose a heterogeneous time-sensitive network(HTSN) co-designed by 5 G and TSN. We first develop a predictive multi-priority wireless scheduling mechanism based on semi-persistent scheduling(SPS) to reduce signaling delay by reserving resources in *** we propose an adaptive data injection mechanism for TSN based on per-stream filtering and policing(PSFP), which dynamically adjusts the priority of data for queue injection in TSN. To further reduce the long tail of delay, we employ a risk-sensitive learning method to improve the worst-case delay. Simulations on a hot rolling production scenario demonstrate that the proposed mechanisms under HTSN achieve great performance in terms of integrated delay and resource utilization.

关键词： industrial cyber-physical systems (ICPS) 5G-TSN co-design wireless/wired integrated network risk-sensitive reinforcement learning deterministic communication

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Dynamic Event-Triggered control for Multi-Agent Consensus with Relative Output Feedback

Dynamic Event-Triggered Control for Multi-Agent Consensus wi...

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American control Conference (ACC)

作者： Sikang Zhan Xianwei Li Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper studies the consensus problem of linear multi-agent systems (MASs) with relative output measurement on undirected graphs. Output-feedback protocols are designed for both leaderless and leader-follower consensus. Different from [1], dynamic event-triggered sampling strategies are integrated to reduce the communication burdens between agents. Compared with most of the existing results which are based absolute output, the proposed protocols are based on sampled relative output. Finally, a simulation example is provided to illustrate the theoretical results.

关键词： Protocols Decentralized control Numerical simulation Topology Closed loop systems Output feedback Multi-agent systems

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ST-Petri: A Visual Executable Semantic Model for PLC Structured Text Language

ST-Petri: A Visual Executable Semantic Model for PLC Structu...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Xiaoyu Hu Yonghui Liang Shibo Zhu Hui Li Shanying Zhu Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

As very important controllers in automated facto-ries, the correctness and safety of Programmable Logic controller (PLC) and their programs determine the stability of the production process. Structured Text (ST) is one of the most widely used PLC programming languages. However, there are not enough formal semantics and different venders may have their own implementations. In this work, a visual executable semantic model ST-Petri for ST has been proposed. The model uses Petri nets to formally represent ST semantics while using graphs to visualise program control flow. To validate the correctness of the semantic model, we use programs from Github and mutations of existing source programs as a test set to execute and compare the results with the open source OpenPLC platform. Experimental results show that ST-Petri has significant advantages in terms of compilation pass rate and error indication as a semantic model and a ST program compiler.

关键词： Visualization Program processors Semantics Programmable logic devices Petri nets Process control Production Stability analysis Safety Software development management

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H∞ Consensus control for High-Order Fully Actuated Multi-Agent systems with External Disturbances

H∞ Consensus Control for High-Order Fully Actuated Multi-Ag...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Qing-Hao Zhang Jun-Guo Lu Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper investigates the problems of H ∞ consensus control for high-order fully actuated multi-agent systems (HOFAMASs) with external disturbances. By utilizing the characteristics of high-order fully actuated systems (HOFASs), the distributed control protocols are designed, eliminating all nonlinear characteristics of open loop systems while establishing new closed-loop dynamic characteristics. Then, the H ∞ consensus problems of HOFAMASs are addressed. The corresponding parameters to be designed in the distributed control protocols are given by using linear matrix inequalities (LMIs). A novel multi-spacecraft attitude model is proposed based on HOFASs. An illustrative example of the multi-spacecraft attitude model is given, in order to demonstrate the effectiveness and application of the results proposed in this paper.

关键词： Sufficient conditions Protocols Attitude control Open loop systems Consensus control Numerical models Linear matrix inequalities

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