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Global output feedback adaptive stabilization for systems with long uncertain input delay

Science China(Information Sciences) 2023年第1期66卷 326-327页

作者： Zhuping WANG Jingcheng LIU Chao HUANG Hao ZHANG Huaicheng YAN School of Electronics and Information Engineering Tongji University Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology

Dear editor,The uncertain input delay is frequently encountered in engineering control systems. Adaptation is indispensable when the uncertain input delay is significant. In existing delayadaptive controllers [1–6], the actuator state must be measured to achieve global stability. Recently, a logic-based switching delay-adaptive state-feedback controller [7] was proposed to realize global stability without measuring the actuator state.

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Causal reasoning in typical computer vision tasks

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Science China(Technological Sciences) 2024年第1期67卷 105-120页

作者： ZHANG KeXuan SUN QiYu ZHAO ChaoQiang TANG Yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China National Key Laboratory of Air based Information Perception and Fusion Luoyang 471000China Luoyang Institute of Electro Optical Equipment of Avic Luoyang 471000China

Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled *** the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious *** a result,researchers are now trying to enhance deep learningbased methods with causal *** theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious *** paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image *** advantages of causality and the approaches for building causal paradigms will be *** roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.

关键词： causal reasoning computer vision tasks vision-language tasks semantic segmentation object detection

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Prescribed-time distributed localization of multi-agent systems based on local bearing information 43

Prescribed-time distributed localization of multi-agent syst...

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43rd Chinese control Conference, CCC 2024

作者： Lv, Yunkai Yan, Huaicheng Rao, Kai Yang, Penghui East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education Shanghai200237 China

ISBN: (纸本)9789887581581

This work considers the localizability of multi-agent systems based on local bearing measurement. A novel prescribed-time orientation estimation algorithm is first proposed to guarantee that the local reference frame of the follower agent is aligned with the global one. The orientation estimation algorithm is then applied to the problem of position estimation, and a prescribed-time distributed localization estimation algorithm is deigned. The global convergence is derived based on the cascade system. Some simulation results are provided to prove the effectiveness of the proposed estimation methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Local bearing information orientation estimation prescribed-time

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Prescribed-time distributed localization of multi-agent systems based on local bearing information

Prescribed-time distributed localization of multi-agent syst...

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第43届中国控制会议

作者： Yunkai Lv Huaicheng Yan Kai Rao Penghui Yang Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This work considers the localizability of multi-agent systems based on local bearing measurement.A novel prescribedtime orientation estimation algorithm is first proposed to guarantee that the local reference frame of the follower agent is aligned with the global *** orientation estimation algorithm is then applied to the problem of position estimation,and a prescribedtime distributed localization estimation algorithm is *** global convergence is derived based on the cascade *** simulation results are provided to prove the effectiveness of the proposed estimation methods.

关键词： Local bearing information orientation estimation prescribed-time

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Robust PD-type iterative learning control design for uncertain batch processes subject to nonrepetitive disturbances 41

Robust PD-type iterative learning control design for uncerta...

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第41届中国控制会议

作者： Robert Maniarski Wojciech Paszke Shoulin Hao Hongfeng Tao Institute of Automation Electronic and Electrical EngineeringUniversity of Zielona Góra Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper develops PD-type iterative learning control schemes for a class of uncertain batch processes subject to nonrepetitive *** means of two-dimensional/repetitive setting,the sufficient conditions for batch-to-batch error convergence and H disturbance attenuation are formulated and ***,the procedure for computing the desired control law matrices is formulated in terms of solvability of linear matrix *** proposed control law is able to fulfil the imposed design specifications,i.e.,they are suitable for the batch processes with time-varying uncertainties as well as non-repetitive *** illustrative example is used to validate the proposed control scheme and demonstrates a possible applicability of the developed results.

关键词： iterative learning control repetitive processes batch processes robust control nonrepetitive disturbances

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Review on electrochemical carbon dioxide capture and transformation with bipolar membranes

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Chinese Chemical Letters 2023年第8期34卷 114-129页

作者： Jinyun Xu Guoqiang Zhong Minjing Li Di Zhao Yu Sun Xudong Hu Jiefang Sun Xiaoyun Li Wenju Zhu Ming Li Ziqi Zhang Yu Zhang Liping Zhao Chunming Zheng Xiaohong Sun School of Chemical Engineering Tianjin Key Laboratory of Green Chemical Technology and Process EngineeringState Key Laboratory of Separation Membrane and Membrane ProcessesTiangong UniversityTianjin 300387China School of Materials Science and Engineering Key Laboratory of Advanced Ceramics and Machining TechnologyMinistry of EducationTianjin UniversityTianjin 300072China Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food poisoning Beijing Center for Disease Prevention and ControlBeijing 100013China Advanced Materials Research Laboratory CNOOC Tianjin Chemical Research and Design InstituteTianjin 300131China

Anthropogenic carbon dioxide(CO_(2))emission from the combustion of fossil fuels aggravates the global greenhouse *** implementation of CO_(2)capture and transformation technologies have recently received great attention for providing a pathway in dealing with global climate *** these technologies,electrochemical CO_(2)capture technology has attracted wide attention because of its environmental friendliness and flexible operating *** membranes(BPMs)are considered as one of the key components in electrochemical devices,especially for electrochemical CO_(2)reduction and electrodialysis *** create an alkaline environment for CO_(2)capture and a stable pH environment for electrocatalysis on a single *** key to CO_(2)capture in these devices is to understand the water dissociation mechanism occurring in BPMs,which could be used for optimizing the operating conditions for CO_(2)capture and *** this paper,the references and technologies of electrochemical CO_(2)capture based on BPMs are reviewed in detail,thus the challenges and opportunities are also discussed for the development of more efficient,sustainable and practical CO_(2)capture and transformation based on BPMs.

关键词： Bipolar membranes Carbon dioxide Electrochemical capture Transformation CO_(2)reduction Electrodialysis devices Water dissociation

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Identification of Abnormal Operating Conditions in Fused Magnesium Furnaces Using a Deep Multiview TSK Fuzzy System

Identification of Abnormal Operating Conditions in Fused Mag...

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2024 China Automation Congress, CAC 2024

作者： Xi, Chao Wu, Gaochang Fan, Zizhu Xu, Feng Wang, Hui Tang, Xiaokun School of Electrical and Automation Engineering East China Jiaotong University Nanchang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China College of Computer Science and Technology Shanghai University of Electric Power Shanghai China Key Laboratory of Advanced Control and Optimization of Jiangxi Province East China Jiaotong University Nanchang China

ISBN: (纸本)9798350368604

The smelting process of the fused magnesium furnace(FMF) is prone to semi-molten abnormal conditions, which may lead to low product quality and production efficiency, and is also prone to safety accidents. At present, the operating conditions of FMF mainly rely on manual observation of the furnace shell features for diagnosis, and it is hard to timely and effectively identify abnormalities in the smelting process. Given the difficulty in identifying abnormal operating conditions of FMF, this paper proposes a deep multiview fuzzy classification method(DMFC) that can automatically identify abnormal operating conditions. First, based on the three-phase current data, CNN and Transformer are used to extract features as multiple views. Secondly, the Takagi-Sugeno-Kang(TSK) fuzzy model is used as a single-view model, and the evidence theory is used for dynamic fusion of multiple views. This method can effectively fuse multiple deep features, and has strong scalability and a certain degree of interpretability. Through verification of the real historical data of multiple FMFs, our model has relatively high accuracy, false detection rate(FDR), and missed detection rate(MDR). © 2024 IEEE.

关键词： Smelting

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Coupling pinch analysis and rigorous process simulation for hydrogen networks with light hydrocarbon recovery

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Chinese Journal of Chemical Engineering 2021年第12期34卷 141-148页

作者： Minbo Yang Xiao Feng Liang Zhao Shaanxi Key Laboratory of Energy Chemical Process Intensification School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi'an 710049China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of EducationShanghai 200237China

In refineries,some hydrogen-rich streams contain considerable light hydrocarbons that are important raw materials for the chemical *** hydrogen networks with light hydrocarbon recovery can enhance the reuse of both hydrogen and light *** work proposes an automated method for targeting hydrogen networks with light hydrocarbon recovery.A pinch-based algebraic method is improved to determine the minimum fresh hydrogen consumption and hydrogen sources fed into the light hydrocarbon recovery unit *** process simulation is conducted to determine the mass and energy balances of the light hydrocarbon recovery *** targeting procedures are developed through combination of the improved pinch method and rigorous process *** hybrid method is realized by coupling the Matlab and Aspen HYSYS platforms.A refinery hydrogen network is analyzed to illustrate application of the proposed *** integration of hydrogen network with light hydrocarbon recovery further reduces fresh hydrogen requirement by463.0 m^(3)·h^(-1) and recovers liquefied petroleum gas and gasoline of 1711.5 kg·h^(-1) and 643 kg·h^(-1),respectively.A payback period of 9.2 months indicates that investment in light hydrocarbon recovery is economically attractive.

关键词： Hydrogen Light hydrocarbon recovery Pinch technology Simulation Systems engineering

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Causal reasoning in typical computer vision tasks

arXiv

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arXiv 2023年

作者： Zhang, Kexuan Sun, Qiyu Zhao, Chaoqiang Tang, Yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based methods, computer vision has contributed to tremendous growth in areas like autonomous driving and robotics. Despite being the basis of deep learning, such correlation is not stable and is susceptible to uncontrolled factors. In the absence of the guidance of prior knowledge, statistical correlations can easily turn into spurious correlations and cause confounders. As a result, researchers are now trying to enhance deep learning methods with causal theory. Causal theory models the intrinsic causal structure unaffected by data bias and is effective in avoiding spurious correlations. This paper aims to comprehensively review the existing causal methods in typical vision and vision-language tasks such as semantic segmentation, object detection, and image captioning. The advantages of causality and the approaches for building causal paradigms will be summarized. Future roadmaps are also proposed, including facilitating the development of causal theory and its application in other complex scenes and systems. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Monocular depth estimation based on deep learning: An overview

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Science China(Technological Sciences) 2020年第9期63卷 1612-1627页

作者： ZHAO ChaoQiang SUN QiYu ZHANG ChongZhen TANG Yang QIAN Feng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on feature correspondences of multiple viewpoints. Meanwhile, the predicted depth maps are sparse. Inferring depth information from a single image(monocular depth estimation) is an ill-posed problem. With the rapid development of deep neural networks, monocular depth estimation based on deep learning has been widely studied recently and achieved promising performance in accuracy. Meanwhile, dense depth maps are estimated from single images by deep neural networks in an end-to-end manner. In order to improve the accuracy of depth estimation, different kinds of network frameworks, loss functions and training strategies are proposed subsequently. Therefore, we survey the current monocular depth estimation methods based on deep learning in this review. Initially, we conclude several widely used datasets and evaluation indicators in deep learning-based depth estimation. Furthermore, we review some representative existing methods according to different training manners: supervised, unsupervised and semi-supervised. Finally, we discuss the challenges and provide some ideas for future researches in monocular depth estimation.

关键词： autonomous systems monocular depth estimation deep learning unsupervised learning

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