检索结果-内蒙古大学图书馆

IEEE International Conference on Robotics and Biomimetics

作者： Haocheng Huang Zhengyan Zhang Zhe Min Max Q.-H. Meng Shuang Song Jiaole Wang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China School of Control Science and Engineering Shandong University Jinan China Department of Electronic and Electrical Engineering Southern University of Science and Technology in Shenzhen China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Shenzhen Research Institute of the Chinese University of Hong Kong in Shenzhen China

Non-rigid point set registration is an essential technique in fields such as robotics, computer vision, image-guided surgery, and augmented reality. However, effectively addressing non-rigid deformations and handling noise interference remains a significant challenge in this context. This paper introduces a novel hybrid mixture model (HMM), combining a Gaussian mixture model (GMM) to describe positional features and a Fisher mixture model (FMM) to represent orientation features. This hybrid mixture model offers a solution to the non-rigid point set registration (PSR) problem. The proposed approach iteratively optimizes model parameters through the maximum expectation (EM) algorithm. It comprehensively explores registration performance, accounting for non-rigid deformations amidst isotropic and anisotropic positional noise. The proposed approach further incorporates reliable normal vectors for evaluating orientation features. Extensive experiments on non-rigid PSR demonstrates the improvements our algorithm offers in terms of both robustness and accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Generalized negative imaginary synthesis for attitude stabilization of flexible satellites with negative imaginary uncertainty

引用

Journal of the Franklin institute 2025年第11期362卷

作者： Cheng, Zhining Meng, Fanwei He, Zhen Xie, Jiaxiang Department of Control Science and Engineering School of Astronautics Harbin Institute of Technology Harbin 150001 China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao 066004 China

This paper studies the attitude control of a class of flexible satellites with negative imaginary (NI) uncertainty and proposes a new NI synthesis method for linear time invariant (LTI) system with two poles at the origin. Firstly, a dynamic parallel feedforward compensator is added to the controlled plant, which ensures that the augmented system exhibits negative imaginary property. Furthermore, a set of linear matrix inequalities (LMIs) conditions are derived, leading to easy application of this scheme. Secondly, a nonlinear numerical optimization method is adopted to design a set of strictly negative imaginary (SNI) controllers. An integral resonant controller is designed with internal stability and the worst-case H2 norm of the closed-loop system minimized. Finally, a two-body flexible satellite simulation experiment is carried out to verify the effectiveness of the proposed method. The results show that the robust stability of the scheme is significantly better than that of the traditional robust control scheme in the case of parameter perturbation or unmodeled dynamics.

关键词： Feedforward compensation Flexible satellite Negative imaginary uncertainty Nonlinear numerical optimization Strictly negative imaginary controller

来源：评论

学校读者我要写书评

暂无评论

An Approach for Rapid Online Robustness Enhancement of Distributed Power Systems using Load Classifier Forecasting

An Approach for Rapid Online Robustness Enhancement of Distr...

引用

International (EPE-PEMC) Power Electronics and Motion control Conference

作者： Xin Wei Denis Sidorov Aliona Dreglea Alexey Iskakov Zongjie Wang Liguo Wang School of Electrical Engeering & Automation Harbin Institute of Technology Harbin China Energy Systems Institute of Russian Academy of Sciences Irkutsk Russia Baikal School of BRICS Irkutsk National Research Technical University Irkutsk Russia V.A.Trapeznikov Institute of Control Sciences Russian Academy of Sciences Moscow Russia Electrical and Computer Engineering Department University of Connecticut Storrs US

ISBN: (数字)9798350385236

ISBN: (纸本)9798350385243

In this paper, we propose an online approach to rapidly and efficiently improve the robustness of distributed power systems (DPSs). Based on real-time monitoring of sudden voltage sag the main work includes the following two steps: offline classifier identification and online instantaneous disturbance suppression. In order to accurately forecast load classifiers, we adopt an automatic analytical solution, Wu’s Elimination Method (WEM), to derive the expressions of differential equations that are used to describe the phenomena in DPS. Then the corresponding load classifiers have been obtained by BCU method (Boundary of stability region based controlling Unstable equilibrium point method). The optimum switching time of the proposed Active Damping Generator can be chosen based on combining the obtained classifiers with digital signal processing. Simulation and experimental results show that through our work the suddenly changed voltage and distorted current of the DPS can be quickly recovered within 15ms which is faster than the standard IEC TS62749-2015.

关键词： Damping Power quality Signal processing algorithms Power system stability Robustness Generators Real-time systems Classification algorithms Surges Standards

来源：评论

学校读者我要写书评

暂无评论

基于自解耦三明治结构的横向运动栅场效应晶体管MEMS微力传感器

引用

engineering 2023年第2期21卷 61-74,M0004页

作者：高文迪乔智霞韩香广王小章 Adnan Shakoor 刘存朗卢德江杨萍赵立波王永录王久洪蒋庄德孙东 State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150006China Eleventh Research Institute Sixth Academy of China Aerospace Science and Technology Co.Xi’an 710100China Department of Control and Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Biomedical Engineering City University of Hong KongHong Kong 999077China

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵... 详细信息

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵列层和两个软光阻层SU-8组成。通过所提出的双差分传感结构,LMGFET横向工作在垂直干扰下的输出电流被大大消除,所提出传感器的相对输出误差从4.53%(传统差分结构)降低到0.01%。提出了一种实用的传感器制造工艺,并对其进行了模拟。基于LMGFET的力传感器的灵敏度为4.65μA·nN^(-1),可与垂直可移动栅极场效应晶体管(VMGFET)器件相媲美,但非线性度提高了0.78%,测量范围扩大了±5.10μN。这些分析为LMGFET器件的电气和结构参数提供了全面的设计优化,并证明了所提出的传感器在生物医学显微操作应用中具有良好的力传感潜力。

关键词：力传感器场效应晶体管横向运动三明治结构电气模型显微操作非线性度双差分

来源：评论

学校读者我要写书评

暂无评论

Random Forest Regression for Battery State-of-Health Estimation Based on Unsupervised Transfer Component Analysis Domain Adaptation

Random Forest Regression for Battery State-of-Health Estimat...

引用

IEEE International Conference on Industrial technology (ICIT)

作者： Jilun Tian Jiusi Zhang Congsheng Huangy Mo-Yuen Chowz Hao Luo Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan R.O.C. Department of Electrical and Computer Engineering North Carolina State University Raleigh NC U.S.A.

ISBN: (纸本)9781728119496

Machine learning is an useful approach estimating the state-of-health (SOH) of the lithium-ion batteries and had been successfully implemented on battery management systems (BMS). However, the SOH estimation accuracy of the machine learning relies highly on the similarity of training dataset and battery data of estimation. In other words, the machine learning approach may fail if the battery of estimation is operated in a different condition from the condition set for collecting the training dataset. This paper aims on solving such a problem by proposing a transfer component analysis-random forest regression (TCA-RF) approach. The robustness of this proposed approach is ensured by the random forest regression, which is an ensemble learning approach. The generalization of this proposed approach is enhanced by transfer component analysis since it achieves the domain adaption with well transformation of features between two datasets. Two battery ageing datasets collected in different operating conditions are selected in this paper to validate the success of the proposed work, where these two datasets are collected by the Center for Advanced Life Cycle engineering (CALCE) and the National Aeronautics and Space Administration (NASA) Prognostics Center of Excellence (PCoE). The proposed work is further compared with multiple commonly adopted intelligent algorithms to showcase the high performance of the proposed work. The experimental results shows that the proposed TCA-RF approach has a better accurate SOH estimation comparing to other estimation algorithms by 2% to more 50%.

关键词： Training Radio frequency NASA Transfer learning Estimation Forestry Robustness

来源：评论

学校读者我要写书评

暂无评论

Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation

arXiv

引用

arXiv 2021年

作者： Bai, Mingliang Zhao, Xinyu Long, Zhenhua Liu, Jinfu Yu, Daren Department of Control Science and Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China School of Energy Science and Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China

Solar energy is a clean and renewable energy. Photovoltaic (PV) power is an important way to utilize solar energy. Accurate PV power forecast is crucial to the large-scale application of PV power and the stability of electricity grid. This paper proposes a novel method for short-term photovoltaic power forecast using deep convolutional long short-term memory (ConvLSTM) network and kernel density estimation (KDE). In the proposed method, ConvLSTM is used to forecast the future photovoltaic power and KDE is used for estimating the joint probabilistic density function and giving the probabilistic confidence interval. Experiments in an actual photovoltaic power station verify the effectiveness of the proposed method. Comparison experiments with convolutional neural network (CNN) and long short-term memory network (LSTM) shows that ConvLSTM can combine the advantages of both CNN and LSTM and significantly outperform CNN and LSTM in terms of forecast accuracy. Through further comparison with other five conventional methods including multilayer perceptron (MLP), support vector regression (SVR), extreme learning machine (ELM), classification and regression tree (CART) and gradient boosting decision tree (GBDT), ConvLSTM can significantly improve the forecast accuracy by more than 20% for most of the five methods and the superiorities of ConvLSTM are further verified. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Enhanced Removal of Ni-Edta by Three-Dimensional Electro-Fenton Process Using Fe-N-Doped Biochar as Catalytic Particle Electrodes

SSRN

引用

SSRN 2023年

作者： Zhao, Zilong Ren, Yatao Qi, Shuyu Ning, Zigong Wang, Xing Dong, Wenyi Wang, Hongjie School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen Shenzhen518055 China CAS Key Laboratory of Urban Pollutant Conversion Department of Environmental Science and Engineering University of Science and Technology of China Hefei230026 China Shenzhen Key Laboratory of Water Resource Utilization and Environmental Pollution Control Shenzhen518055 China State Key Laboratory of Urban Water Resource and Environment School of Environment Harbin Institute of Technology Harbin150090 China School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen Xili University Town Nanshan District Shenzhen518055 China

Heavy metal complexes are refractory to be removed due to their stable and intricate structure. In this work, Fe and N co-doped biochar derived from rice husk (Fe-N-RHBC) was exploited as catalytic particle electrodes in a three-dimensional electro-Fenton (3D-EF) system for the decomplexation and removal of Ni-EDTA model pollutant. The characterization analysis and catalytic activity comparison verified the enhancement effects of Fe and N co-doping on the types of active sites, interfacial electron transfer property, and H2O2 decomposition capacity. Compared with other oxidation systems studied, rapid removal of Ni-EDTA could be achieved by 3D-EF within the initial 1 minutes, with the maximum H2O2 utilization up to 99.1% after 30 min. After three consecutive cycles, the as-prepared catalytic particle electrodes still retained high stability and catalytic capacity. During the reaction, anode oxidation, particle electrode polarization, catalysis and adsorption of Fe-N-RHBC as well as cathodic electro-deposition worked together to contribute to the treatment of Ni-EDTA, and the surface-bound O2•− radicals and 1O2 induced by Fe-N-RHBC catalytic particle electrode were the primary responsibility for decomplexation and removal of Ni-EDTA. On this basis, the possible mechanisms of Ni-EDTA removal in the 3D-EF by Fe-N-RHBC catalytic particle electrode were further proposed. © 2023, The Authors. All rights reserved.

关键词： Catalyst activity

来源：评论

学校读者我要写书评

暂无评论

Waste sludge disintegration, methanogenesis and final disposal via various pretreatments: Comparison of performance and effectiveness

引用

Environmental Science and Ecotechnology 2021年第4期8卷 119-129页

作者： Haiyang He Xiaodong Xin Wei Qiu Dong Li Zhicen Liu Jun Ma State Key Laboratory of Urban Water Resource and Environment School of EnvironmentHarbin Institute of TechnologyHarbin150090China Department of Environmental Science and Engineering Huaqiao UniversityXiamen361021China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlSchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjing210044China School of Geosciences The University of EdinburghEdinburghEH89JUUK

This study compared the three wastewater pretreatments of ozonation,Fe2þ-S2O82and freeze-thawing(F/T)in the disintegration,anaerobic digestion(AD)and final disposal of the *** F/T pretreatment increased the dewaterability and settleability of the sludge by 7.8%and 47.1%,*** ozonation pretreatment formed more volatile fatty acids(VFAs),with a peak value of 320.82 mg SCOD/L and controlled the release of *** Fe2þ-S2O82pretreatment removed heavy metals through the absorption and flocculation of ferric particles formed *** the anaerobic digestion of the sludge,the ozonation pretreatment accelerated the hydrolysis rate(k)rather than the biochemical methane potential(B0)of the sludge due to the high VFA content in the ***,the F/T pretreatment facilitated the B0 with great economic efficiency by enhancing the solubilisation of the *** Fe2þ-S2O82pretreatment decreased the methane production,the ferric particle was a unique advantage in the disintegration and harmless disposal of the *** digested sludge had more VFAs after ozonation pretreatment,which contributed to the recycling of *** addition,the lower sludge volume could save the expense of transportation and disposal by ozonation *** pretreatments had different *** comparative study provided information allowing the selection of the type of pretreatment to achieve different objectives of the treatment and disposal of sludge.

关键词： Sludge disintegration Anaerobic sludge digestion Effectiveness comparison Different pretreatments

来源：评论

学校读者我要写书评

暂无评论

Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation

arXiv

引用

arXiv 2023年

作者： Li, Shilei Shi, Dawei Lou, Yunjiang Zou, Wulin Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Xeno Dynamics Control Department Xeno Dynamics Co. Ltd Shenzhen518055 China

Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, The noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ones. To handle this issue, we propose a generalized multi-kernel maximum correntropy Kalman filter for disturbance estimation, which is less conservative by adopting different kernel bandwidths for different channels and exhibits excellent performance both with and without external disturbance. The convergence of the fixed point iteration and the complexity of the proposed algorithm are given. Simulations on a robotic manipulator reveal that the proposed algorithm is very efficient in disturbance estimation with moderate algorithm complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Distributed Observer for A Class of Discrete-Time Uncertain Linear Systems over Acyclic Digraphs

An Adaptive Distributed Observer for A Class of Discrete-Tim...

引用

IEEE Conference on Decision and control

作者： Tao Liu Jie Huang Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China Shenzhen Research Institute and Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin N.T. Hong Kong

This paper proposes an adaptive distributed observer for a class of discrete-time uncertain linear leader systems. The leader system is assumed to be neutrally stable with unknown parameters in the system matrix. Such a leader system can produce multi-tone sinusoidal signals with unknown frequencies, magnitudes, and phases. Under the assumption that the digraph of the communication network is a spanning tree with the leader system as the root, the proposed adaptive distributed observer is shown to be capable of estimating over the communication network not only the leader's state, but also the unknown parameters of the leader's system matrix.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：