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A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode control of n-DOF Upper-Limb Exoskeleton With Input Deadzone

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 760-781页

作者： Dingxin He HaoPing Wang Yang Tian Yida Guo the School of Automation Nanjing University of Science and TechnologyNanjing 210094China IEEE Norinco group Institute of Navigation and control Technology Beijing 100089China

This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input *** the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller ***,the control gain of ultra-local model is considered as a *** fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped ***,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is ***,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown ***,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown ***,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is ***,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov ***,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method.

关键词： Adaptive control input deadzone model-free control n-DOF upper-limb exoskeleton neural network

Detection of Oscillations in Process control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

Adaptive battery thermal management systems in unsteady thermal application contexts

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Journal of Energy Chemistry 2024年第10期97卷 650-668页

作者： Kailong Liu Qiao Peng Zhuoran Liu Wei Li Naxin Cui Chenghui Zhang School of control Science and Engineering Shandong University Information Technology Analytics & Operations Group Queen's University Belfast College of Design and Engineering National University of Singapore

With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial ***,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is *** the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management *** battery thermal management systems have basic temperature control capabilities for most conventional application ***,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating *** this context,this paper presents the latest advances and representative research related to battery thermal management ***,starting from battery thermal profile,the mechanism of battery heat generation is discussed in ***,the static characteristics of the traditional battery thermal management system are ***,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research ***,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.

关键词： Battery safety Battery thermal management system Cooling methods Heat generation mechanism Lithium-ion batteries

An Embedded Consensus ADMM Distribution Algorithm Based on Outer Approximation for Improved Robust State Estimation of Networked

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1217-1226页

作者： Zifeng Zhang Yuntao Ju State Grid Information&Telecommunication group Co. Ltd.Beijing BranchBejingChina School of Electrical and control Engineering North China University of TechnologyBeijingChina

Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable ***,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy *** currentestimator is also not robust against bad *** study introducesthe concepts of relative error to construct an improvedrobust SE(IRSE)optimization model with mixed-integer nonlinearprogramming(MINLP)that overcomes the disadvantage ofinaccurate results derived from different measurements whenthe same tolerance range is considered in the robust SE(RSE).To improve the computation efficiency of the IRSE optimizationmodel,the number of binary variables is reduced based on theprojection statistics and normalized residual methods,which effectivelyavoid the problem of slow convergence or divergenceof the algorithm caused by too many integer ***,an embedded consensus alternating direction of multiplier method(ADMM)distribution algorithm based on outer approximation(OA)is proposed to solve the IRSE optimization *** algorithm can accurately detect bad data and obtain SE resultsthat communicate only the boundary coupling informationwith *** tests show that the proposed algorithmeffectively detects bad data,obtains more accurate SE results,and ensures the protection of private information in all microgrids.

关键词： Distributed optimization alternating direction of multiplier methods(ADMM) robust state estimation(RSE) mixed-integer nonlinear programming(MINLP) networked microgrid(NMG)

Explainable Neural Network for Sensitivity Analysis of Lithium-ion Battery Smart Production

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1944-1953页

作者： Kailong Liu Qiao Peng Yuhang Liu Naxin Cui Chenghui Zhang School of control Science and Engineering Shandong UniversityJinan 250061China Information Technology Analytics&Operations groupQueen’s University BelfastBelfast BT71NNUK

Battery production is crucial for determining the quality of electrode,which in turn affects the manufactured battery *** battery production is complicated with strongly coupled intermediate and control parameters,an efficient solution that can perform a reliable sensitivity analysis of the production terms of interest and forecast key battery properties in the early production phase is urgently *** paper performs detailed sensitivity analysis of key production terms on determining the properties of manufactured battery electrode via advanced data-driven *** be specific,an explainable neural network named generalized additive model with structured interaction(GAM-SI)is designed to predict two key battery properties,including electrode mass loading and porosity,while the effects of four early production terms on manufactured batteries are explained and *** experimental results reveal that the proposed method is able to accurately predict battery electrode properties in the mixing and coating *** addition,the importance ratio ranking,global interpretation and local interpretation of both the main effects and pairwise interactions can be effectively visualized by the designed neural *** to the merits of interpretability,the proposed GAM-SI can help engineers gain important insights for understanding complicated production behavior,further benefitting smart battery production.

关键词： Battery management battery manufacturing data science explainable artificial intelligence sensitivity analysis

Numerical simulation research on multiphase flow of aviation centrifugal pump based on OpenFOAM

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Chinese Journal of Aeronautics 2024年第4期37卷 256-275页

作者： Xianwei LIU Jiangfeng FU Junjie YANG Dewen YIN Zhenhua ZHOU Huacong LI College of Power and Energy Northwestern Polytechnical UniversityXi’an 710072China Norinco group Testing and Research Institute Huayin 714200China AECC Xi’an Engine control Technology Co.Ltd. Xi’an 710077China AECC Guizhou Honglin Aero Engine control Technology Co.Ltd. Guiyang 550009China

This paper aims to tackle the calculation efficiency problem raised in the cavitation-flow simulation of the aviation centrifugal pump due to the fading-away interface resulting from the dissipation of numerics used in the phase-change control equation for unstructured-grid multiphase flow,and due to the limitation of flow time-step in whole flow regimes,the control equation of vapor–liquid two-phase flow considering cavitation mass transport is established firstly,modifying the momentum equation by introducing the surface tension,and adding the artificial convective flow to the phase equation to solve the numerical dissipation ***,in consideration of the local time step principle and based on the multi-dimensional general limiter algorithm with explicit solutions under the OpenFOAM platform,a solution method of steady-state VOF (Volume of Fluid) model considering cavitation two-phase change is constructed,and the feasibility of this method is verified by NACA hydrofoil and NASA flat plate ***,based on the platform developed,the cavitation performance of an aviation centrifugal pump inducer is *** research results show that the error of the calculated cavitation pressure distribution for NACA hydrofoil between the simulation test and the experimental-test is less than 5%,and the maximum error of calculated cavitation number at pump head dropping for NASA high-speed flat plate inducer between the simulation test and the experimental-test is 2.1%.The cavitation area observed in the simulation test is the same as that obtained in the high-speed photography *** on the OpenFOAM simulation method,the position of pump head dropping of the fuel centrifugal pump can be accurately *** error of the calculated cavitation number at pump head dropping between the simulation test and the experimental test is about 3.7%,showing high calculation accuracy.

关键词： Aero engine Fuel centrifugal pump Multiphase flow OpenFOAM Volume of fluid

Pathway Planning of Nuclear Power Development Incorporating Assessment of Nuclear Event Risk

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 500-513页

作者： Xinxin Yang Yusheng Xue Bin Cai School of Electrical Engineering Southeast UniversityNanjingChinaand they are also with State Grid Electric Power Research Institute(NARI Group Corporation)NanjingChina State Key Laboratory of Smart Grid Protection and Operation control NanjingChina State Grid Electric Power Research Institute(NARI group Corporation) NanjingChina

The nuclear event risk(NER)is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development(NPD)to assess the benefits and risks of developing nuclear power more *** paper aims to explore the impact of nuclear events on NPD pathway *** influence of nuclear events is quantified as a monetary risk component,and an optimization model that incorporates the NER in the objective function is *** optimize the pathway of NPD in the lowcarbon transition course of power supply structure evolution,a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway(CEP);moreover,a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction(CER)component,and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies.A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway *** method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.

关键词： Low-carbon transition power supply structure evolution nuclear power development(NPD) quantitative analysis nuclear event risk evaluation

Regression Method for Rail Fastener Tightness Based on Center-Line Projection Distance Feature and Neural Network

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 356-371页

作者： Yuanhang Wang Duxin Liu Sheng Guo Yifan Wu Jing Liu Wei Li Hongjie Wang Robotics Research Center School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China China Construction Industrial&Energy Engineering group Co. Ltd.Nanjing 210023China

In the railway system,fasteners have the functions of damping,maintaining the track distance,and adjusting the track ***,routine maintenance and inspection of fasteners are important to ensure the safe operation of track ***,assessment methods for fastener tightness include manual observation,acoustic wave detection,and image *** are limitations such as low accuracy and efficiency,easy interference and misjudgment,and a lack of accurate,stable,and fast detection *** at the small deformation characteristics and large elastic change of fasteners from full loosening to full tightening,this study proposes high-precision surface-structured light technology for fastener detection and fastener deformation feature extraction based on the center-line projection distance and a fastener tightness regression method based on neural ***,the method uses a 3D camera to obtain a fastener point cloud and then segments the elastic rod area based on the iterative closest point algorithm *** component analysis is used to calculate the normal vector of the segmented elastic rod surface and extract the point on the centerline of the elastic *** point is projected onto the upper surface of the bolt to calculate the projection ***,the mapping relationship between the projection distance sequence and fastener tightness is established,and the influence of each parameter on the fastener tightness prediction is ***,by setting up a fastener detection scene in the track experimental base,collecting data,and completing the algorithm verification,the results showed that the deviation between the fastener tightness regression value obtained after the algorithm processing and the actual measured value RMSE was 0.2196 mm,which significantly improved the effect compared with other tightness detection methods,and realized an effective fastener tightness regression.

关键词： Railway system Fasteners Tightness inspection Neural network regression 3D point cloud processing

Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

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Rice science 2024年第1期31卷 6-9,I0009-I0012页

作者： YANG Sen WANG Zhenmin ZHANG Houqing SONG Wenlong College of Computer and control Engineering Northeast Forestry UniversityHarbin 150040China The 49th Research Institute of China Electronics Technology group Corporation Harbin 150000China

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice *** the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were *** enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).

关键词： sealing Infrared grinding