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Anti-saturation fault-tolerant adaptive torsional vibration control with fixed-time prescribed performance for rolling mill main drive system

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Journal of Iron and Steel research International 2024年第3期31卷 660-669页

作者： Shuang Liu Chen Du Cong Zhang Zhen-hua Bai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004HebeiChina National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004HebeiChina

An anti-saturation fault-tolerant adaptive torsional vibration control method with fixed-time prescribed performance for the rolling mill main drive system(RMMDS)was investigated,which is affected by control input saturation,actuator faults,sensor measurement errors,and parameter ***,we gave a continuously differentiable saturation function to approximate the control input saturation characteristic of the RMMDS,translating the saturation characteristic into the matched uncertainty and unknown time-varying gain in the ***,an RMMDS mathematical model with unmatched uncertainty and unknown time-varying gain was developed,taking into account the presence of control input saturation,actuator faults,sensor measurement errors,and parameter *** on the established mathematical model,an error transformation model of the roll speed tracking was constructed by the equivalent error transformation *** to the error transformation model,a barrier Lyapunov function and a novel adaptive controller were studied to ensure that the roll speed tracking error always evolves inside a fixed-time asymmetric ***,numerical simulations were performed in Matlab/Simulink to verify the effectiveness and superiority of the proposed control method in suppressing the RMMDS torsional vibration.

关键词： Fixed-time prescribed performance Control input saturation Actuator fault Unknown time-varying gain Adaptive control Asymmetric constraint

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On Frequency Sensitivity and Mode Orthogonality of Flexible Robotic Manipulators

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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 394-397页

作者： Fei-Yue Wang Yanqing Gao IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Department of Manufacturing & Mechanical Engineering & Technology Oregon Institute of Technology

This paper presents sensitivity analysis of vibration frequencies of flexible manipulators with respect to variations of systems parameters such as rotational inertia of hub, and mass, moment, and side of tip load. Both Euler-Bernoulli and Timoshenko dynamical models of flexible manipulators are discussed. By using variational method, sensitivity indices are obtained with explicit expressions for measuring the sensitivity of frequencies. Based on variational formulations, a novel method for deriving the orthogonal relations among vibration modal shape functions of flexible manipulators is introduced. With this method, the orthogonal relations can be derived easily without invoking the tedious process of differentiation and integration by part, as commonly used in their derivation. © 2014 Chinese Association of Automation.

关键词： Dielectric waveguides Flexible manipulators Manipulators Orthogonal functions Vibration analysis

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Standard Analysis for Transfer Delay in CTCS-3

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Chinese Journal of Electronics 2017年第5期26卷 1057-1063页

作者： CAO Yuan MA Lianchuan XIAO Shuo ZHANG Xia XU Wei National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Computer Sciences and Technology China University of Mining & Technology National Mobile Communications Research Lab. Southeast University

According to the standard for the GSM for railway(GSM-R) wireless systems in China train control system level 3(CTCS-3),the control data transfer delay should be no larger than 500 ms with greater than99% *** of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals(MTs) and redundant MTs on one train are considered,and the corresponding vehicle-ground communication models,delay models,and fault models are *** simulation results confirm that the transfer delay can meet the standard requirements under all *** particular,the probability is greater than 99.996% for redundant MTs and networks,and the standard of transfer delay in CTCS-3 will be improved inevitably.

关键词： China train control system level 3(CTCS-3) GSM for railway(GSM-R) Data transfer delay Deterministic and stochastic petri net(DSPN)

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A new fragment re-allocation strategy for NoSQL database systems

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Frontiers of computer Science 2015年第1期9卷 111-127页

作者： Zhikun CHEN Shuqiang YANG Shuang TAN Li HE Hong YIN Ge ZHANG Department of Computer Science National University of Defense Technology Chang sha 410073 China Unit 91655 People's Liberation Army Beijing 100036 China Beijing Aeronautics Engineering Technology Research Center Beijing 100076 China

Abstract NoSQL databases are famed for the characteristics of high scalability, high availability, and high faulttolerance. So NoSQL databases are used in a lot of applications. The data partitioning strategy and fragment allocation strategy directly affect NoSQL database systems＇ performance. The data partition strategy of large, global databases is performed by horizontally, vertically partitioning or combination of both. In the general way the system scatters the related fragments as possible to improve operations＇ parallel degree. But the operations are usually not very complicated in some applications, and an operation may access to more than one fragment. At the same time, those fragments which have to be accessed by an operation may interact with each other. The general allocation strategies will increase system＇s communication cost during operations execution over sites. In order to improve those applications＇ performance and enable NoSQL database systems to work efficiently, these applications＇ fragments have to be allocated in a reasonable way that can reduce the communication cost i.e., to minimize the total volume of data transmitted during operations execution over sites. A strategy of clustering fragments based onhypergraph is proposed, which can cluster fragments which were accessed together in most operations to the same cluster. The method uses a weighted hypergraph to represent the fragments＇ access pattem of operations. A hypergraph partitioning algorithm is used to cluster fragments in our strategy. This method can reduce the amount of sites that an operation has to span. So it can reduce the communication cost over sites. Experimental results confirm that the proposed technique will effectively contribute in solving fragments re-allocation problem in a specific application environment of NoSQL database system.

关键词： fragment allocation NoSQL database hypergraph partition clustering fragments fragment correlation

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Automatic text summarization using deep reinforced model coupling contextualized word representation and attention mechanism

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Multimedia Tools and Applications 2024年第1期83卷 733-762页

作者： Aliakbarpour, Hassan Manzuri, Mohammad Taghi Rahmani, Amir Masoud Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Computer Engineering Department Sharif University of Technology Tehran Iran Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan

With the rapid and unprecedented growth of textual data in recent years, there is a remarkable need for automatic text summarization models to retrieve useful information from these large numbers of textual documents without human intervention within a reasonable time. Text summarization is commonly performed based on extractive and abstractive paradigms. Although different machine learning and deep learning based methods have been proposed for the task of text summarization during the last decades, they are still in their early steps of development and their potential has yet to be fully explored. Accordingly, a new summarization model is proposed in this paper which takes advantage of both extractive and abstractive text summarization models as a single unified model based on the strategy gradient of reinforcement learning. The proposed model also employs the combination of convolutional neural network and gated recurrent unit in both extraction and abstraction modules besides attention mechanism. Moreover, language models, namely Word2Vec and BERT, are used as the backbone of the proposed model to better express sentence semantics as a word vector. We conducted our experiments on widely-studied text summarization datasets (CNN\Daily Mail and DUC-2004) and according to the empirical results, not only the proposed model achieved higher accuracy compared to both extractive and abstractive summarization models in terms of ROUGE metric but also its generated summaries presented higher saliency and readability based on human evaluation. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Reinforcement learning

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A NEURAL-NETWORK APPROACH FOR EVALUATING DISTRIBUTION-SYSTEM RELIABILITY

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ELECTRIC POWER SYSTEMS research 1993年第3期26卷 225-229页

作者： CHEN, CL CHEN, JL Department of Electrical Engineering National Taiwan University Taipei Taiwan PRC Advanced Technology Center Computer and Communication Research Laboratories Industrial Technology Research Institute Chutung Hsinchu Taiwan PRC

An effective method for evaluating the distribution system reliability using an artificial neural network (ANN) is proposed in this paper. The ANN is constructed according to the back-propagation learning rule which is an iterative gradient algorithm designed to adjust the interconnection weights among processing elements. Therefore, the developed ANN is used to predict the distribution system reliability using historical data. At the same time, the system average interruption frequency index (SAIFI) and the system average interruption duration index (SAIDI) of a real distribution system are computed and compared with results generated by the network method. It was found that the deviation of the results computed by the proposed approach is below 1% and the required running time on a SUN network environment is less than 2 s. In addition, for handling the distribution system configuration changes induced by overloading or faults, the ANN approach demonstrates an advantage over the network method.

关键词： DISTRIBUTION SYSTEM RELIABILITY ARTIFICIAL NEURAL NETWORK NETWORK METHOD

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Design tradeoffs for data deduplication performance in backup workloads 13

Design tradeoffs for data deduplication performance in backu...

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13th USENIX Conference on File and Storage Technologies, FAST 2015

作者： Fu, Min Feng, Dan Hua, Yu He, Xubin Chen, Zuoning Xia, Wen Zhang, Yucheng Tan, Yujuan Wuhan National Lab for Optoelectronics School of Computer Huazhong University of Science and Technology Wuhan China Dept. of Electrical and Computer Engineering Virginia Commonwealth University VA United States National Engineering Research Center for Parallel Computer Beijing China College of Computer Science Chongqing University Chongqing China

ISBN: (纸本)9781931971201

Data deduplication has become a standard component in modern backup systems. In order to understand the fundamental tradeoffs in each of its design choices (such as prefetching and sampling), we disassemble data deduplication into a large N-dimensional parameter space. Each point in the space is of various parameter settings, and performs a tradeoff among backup and restore performance, memory footprint, and storage cost. Existing and potential solutions can be considered as specific points in the space. Then, we propose a general-purpose framework to evaluate various deduplication solutions in the space. Given that no single solution is perfect in all metrics, our goal is to find some reasonable solutions that have sustained backup performance and perform a suitable tradeoff between deduplication ratio, memory footprints, and restore performance. Our findings from extensive experiments using real-world workloads provide a detailed guide to make efficient design decisions according to the desired tradeoff.

关键词： Restoration

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Roadmap on Neuromorphic Photonics

arXiv

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arXiv 2025年

作者： Brunner, Daniel Shastri, Bhavin J. Al-Qadasi, Mohammed A. Ballani, H. Barbay, Sylvain Biasi, Stefano Bienstman, Peter Bilodeau, Simon Bogaerts, Wim Böhm, Fabian Brennan, G. Buckley, Sonia Cai, Xinlun Strinati, Marcello Calvanese Canakci, B. Charbonnier, Benoit Chemnitz, Mario Chen, Yitong Cheung, Stanley Chiles, Jeff Choi, Suyeon Christodoulides, Demetrios N. Chrostowski, Lukas Chu, J. Clegg, J.H. Cletheroe, D. Conti, Claudio Dai, Qionghai Di Lauro, Luigi Diamantopoulos, Nikolaos-Panteleimon Dinc, Niyazi Ulas Ewaniuk, Jacob Fan, Shanhui Fang, Lu Franchi, Riccardo Freire, Pedro Gentilini, Silvia Gigan, Sylvain Giorgi, Gian Luca Gkantsidis, C. Gladrow, J. Goi, Elena Goldmann, M. Grabulosa, A. Gu, Min Guo, Xianxin Hejda, Matěj Horst, F. Hsieh, Jih-Liang Hu, Jianqi Hu, Juejun Huang, Chaoran Hurtado, Antonio Jaurigue, Lina Kalinin, K.P. Kamalian-Kopae, Morteza Kelly, D.J. Khajavikhan, Mercedeh Kremer, H. Laydevant, Jeremie Lederman, Joshua C. Lee, Jongheon Lenstra, Daan Li, Gordon H.Y. Li, Mo Li, Yuhang Lin, Xing Lin, Zhongjin Lis, Mieszko Lüdge, Kathy Lugnan, Alessio Lupo, Alessandro Lvovsky, A.I. Manuylovich, Egor Marandi, Alireza Marchesin, Federico Massar, Serge McCaughan, Adam N. McMahon, Peter L. Moralis-Pegios, Miltiadis Morandotti, Roberto Moser, Christophe Moss, David J. Mukherjee, Avilash Nikdast, Mahdi Offrein, B.J. Oguz, Ilker Oripov, Bakhrom O'Shea, G. Ozcan, Aydogan Parmigiani, F. Pasricha, Sudeep Pavanello, Fabio Pavesi, Lorenzo Peserico, Nicola Pickup, L. Pierangeli, Davide Pleros, Nikos Porte, Xavier Primavera, Bryce A. Prucnal, Paul Psaltis, Demetri Puts, Lukas Qiao, Fei Rahmani, B. Raineri, Fabrice Ríos Ocampo, Carlos A. Robertson, Joshua Romeira, Bruno Roques-Carmes, Charles Rotenberg, Nir Rowstron, A. Schoenhardt, Steffen Schwartz, Russell L.T. Shainline, Jeffrey M. Shekhar, Sudip Skalli, A. Sohoni, Mandar M. Sorger, Volker J. Soriano, Miguel C. Spall, James Stabile, Ripalta Stiller, Birgit Sunada, Satoshi Tefas, Anastasios Tossoun, Bassem Tsakyridis, Apostolos Turitsyn, Sergei K. Van der Sande, G Université Marie et Louis Pasteur CNRS UMR 6174 Institut FEMTO-ST Besançon25000 France Centre for Nanophotonics Department of Physics Engineering Physics & Astronomy Queen's University Canada Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada Microsoft Research Cambridge United Kingdom Université Paris-Saclay CNRS Centre de Nanosciences et de Nanotechnologies France Nanoscience Laboratory Department of Physics University of Trento Italy Photonics Research Group Department of Information Technology Ghent University imec Belgium Princeton University NJ United States Hewlett Packard Labs Hewlett Packard Enterprise Böblingen Germany National Institute of Standards and Technology BoulderCO United States State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University China Enrico Fermi Research Center Rome Italy Université Grenoble-Alpes CEA Leti Grenoble France Leibniz-Institute of Photonic Technology Jena Germany Institute of Applied Optics and Biophysics Jena Germany Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering North Carolina State University NC United States Department of Electrical Engineering Stanford University CA United States University of Southern California Los AngelesCA United States Department of Physics Sapienza University Rome Italy Institute for Complex Systems National Research Council Rome Italy Varennes Canada NTT Device Technology Labs NTT Corporation Kanagawa Atsugi Japan Institute of Electrical and Microengineering School of Engineering École Polytechnique Fédérale de Lausanne Switzerland Edward L. Ginzton Laboratory Stanford University StanfordCA United States Department of Electronic Engineering Tsinghua University China Beijing National Research Center for Information Science and Technology Tsinghua University China Aston Univ

Neuromorphic photonics are processors inspired by the human brain and enabled by light (photons) instead of traditional electronics. Neuromorphic photonics and its associated concepts are experiencing a significant resurgence, building on foundational research from the 1980s and 1990s. This renewed momentum is driven by breakthroughs in photonic integration, nonlinear optics, and advanced materials, alongside the growing necessity of neuro-inspired computing in numerous applications of economic and societal relevance. The increasing demand for energy-efficient artificial intelligence (AI) solutions underscores the need for innovation and a cohesive vision to address key challenges, including scalability, energy efficiency, precision, and standardized performance benchmarks. Together, these efforts present an opportunity to establish a unique photonic advantage with practical, real-world applications. This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field. The roadmap introduces various approaches to embedding the high-complexity transformations central to neuromorphic computing, focusing on frequency, delay, and spectral embeddings. This is followed by a discussion of architectures of photonic neural networks (PNNs) and an in-depth analysis of methods for implementing these architectures in photonic hardware. Dedicated sections delve into integrated photonic hardware, the realization of photonic weights and memories, and the optimization of training processes for photonic neuromorphic architectures. The roadmap concludes by exploring numerous potential applications, highlighting the challenges and advances necessary to transition neuromorphic photonic computing from a primarily academic pursuit to a technolog

关键词： Philosophical aspects

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research on Information Structure of Programmatic Advertising Markets

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IFAC-PapersOnLine 2017年第1期50卷 13587-13592页

作者： Li, Juanjuan Yuan, Yong Zhao, Xueliang Wang, Fei-Yue The State Key Laboratory of Management Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Beijing Qingdao China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

With the abundance of online big data and computing resources, as well as the rapid develop-ment and diversification of business models, programmatic advertising (PA) has emerged and become the mainstream and one of the most promising advertising channels in recent years. As an effective way to precision marketing, PA relies heavily on the information elicited from analyzing Web users and pages, which can help advertisers precisely identify their best-matched audiences and evaluate the ad impressions in a real-time fashion In PA markets, publishers serve as the supplier of ad impressions, and have control on whether, what and how to reveal such key information to advertisers. These decisions play a central role in the information structure of data-driven PA markets, and attract intensive research interests. In this paper, we strive to investigate publishers’ rational preference over the symmetric and asymmetric information structures, with the aim of maximizing their revenues. Our model views publishers’ revenue as a function of the information structure among advertisers, and we hereby proved its convexity under an incentive compatible mechanism. This conclusion indicates that publishers prefer an asymmetric information structure rather than a symmetric one. Our research findings can help improve publishers’ revenue, and also can explain the underlying rationale for the hybrid PA markets mixed by public real-time bidding and private marketplaces. © 2017

关键词： Commerce Big data Marketing Advertising markets Asymmetric information Computing resource Incentive compatible mechanisms Information structures Precision marketings private marketplace Real time biddings

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Dynamic Multi-scale Feature Integration Network for unsupervised MR-CT synthesis

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Neural Networks 2025年 189卷 107584页

作者： Meng Tang Jiuming Jiang Xue Zhang Tao Zhou Yizhe Zhang Bin Qiu Li Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China Department of Diagnostic Radiology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China Department of Thoracic Surgery National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China

Unsupervised MR-CT synthesis presents a significant opportunity to reduce radiation exposure from CT scans and lower costs by eliminating the need for both MR and CT imaging. However, many existing unsupervised methods face limitations in capturing different anatomical structures due to their inability to model features with large receptive fields, and the receptive fields of different structures can vary. To address this challenge, we propose a novel Dynamic Multi-scale Feature Integration Network (DMFI-Net) tailored for unsupervised MR-CT synthesis. Our DMFI-Net dynamically adjusts its receptive field to extract multi-scale receptive field features, effectively capturing intricate anatomical details to enhance the synthesis performance. Specifically, we present a Global Context-enhanced Kernel Selection (GCKS) module, which intelligently modulates the receptive fields of convolutions for capturing fine-grained details essential to image transformation. By incorporating global cues, the module enriches multi-scale receptive features with comprehensive semantic information, which is crucial for synthesizing globally distributed target regions or organs. Additionally, a Scale Enhancement Module (SEM) is proposed to integrate features extracted with different scales, preserving richer spatial information. Furthermore, we present a scale-aware reconstruction branch to bolster the encoder’s feature extraction capability and improve model generalization. This branch is capable of reconstructing downsampled input images that have undergone random masking, underscoring the model’s robust feature extraction ability. Extensive experimental results on one private and two public MR-CT datasets demonstrate that our model significantly outperforms state-of-the-art MR-CT synthesis methods in both qualitative and quantitative evaluations. The implementation code will be released upon acceptance of this manuscript at https://***/taozh2017/DMFINet .

关键词： Kernel selection Multi-scale feature integration Scale enhancement module Unsupervised MR-CT synthesis

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