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Generalized design approach of a family of grid-connected converters based on active virtual ground technique for single-phase AC microgrid applications

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CPSS Transactions on Power Electronics and Applications 2020年第3期5卷 203-212页

作者： Siu, Ken King Man Ho, Carl Ngai Man Renewable Energy Interface and Grid Automation Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg Canada

The paper presents the state-of-the-art technique Active Virtual Ground (AVG) in the design of single-phase grid-connected converters which fully covers the entire applications on AC microgrids. Based on the three main components of the microgrid, the presented topologies belonging to the AVG series are divided into three different groups, which are associated with power consumers, renewable energy, and energy storage systems. The whole series of the single-phase converters are also based on the latest AVG technique. Therefore, in each application, a corresponding single-stage AVG converter can be found, which has high efficiency, low leakage current, and continuous grid current. The topology advantages and the working principle of the AVG converter family are demonstrated through the circuit evaluation and are experimentally verified in a set of 650 to 800 W prototypes which shows a good agreement on between both of the experimental results and theoretical finding. © 2021 All rights reserved.

关键词： Leakage currents

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Design a High-Frequency Dual Active Bridge Converter for Discrete Time Frequency

Design a High-Frequency Dual Active Bridge Converter for Dis...

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Advancements in electrical, Electronics, Communication, Computing and automation (ICAECA), International Conference on

作者： M. Karthik G. Hemalatha M. Mathankumar L. Sreevidya R. Deepalakshmi V. Kandasamy Department of Electrical and Electronics Engineering SRM Madurai College for Engineering and Technology Pottapalayam Tamil Nadu India Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Trichy Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Computer Science Engineering SRM Madurai College for Engineering and Technology Pottapalayam Tamil Nadu India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

The dual active bridge (DAB) has become a crucial interface element in today's sophisticated systems. Renewable energy sources produce DC power, which is then stored in batteries, ultra-capacitors, and other energy storage devices. DAB is a crucial part of power exchange between two different buses because of its galvanic separation and bidirectional power transfer capabilities. The operation of the DAB is compatible with a broad range of input voltages and output loads. The creation of DAB is covered in most works. A well-known semiconductor integrated circuit with programmable control parameters is used in this straightforward, inexpensive method.

关键词： Time-frequency analysis Renewable energy sources Costs Bridge circuits Switched reluctance motors Stability analysis Batteries Telecommunication computing Time-domain analysis Stress

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A Stable Lithium-ion Battery SOH Estimation Framework for Suppressing Measurement Noise with Unknown Distribution

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IEEE Transactions on Transportation Electrification 2025年

作者： Ma, Wentao Xue, Jingsong Li, Yang Guo, Peng Liu, Xinghua Wei, Zhongbao Wang, Yiwen Chen, Badong Xi’an University of Technology School of Electrical Engineering 710048 China Chalmers University of Technology Department of Electrical Engineering Gothenburg41296 Sweden Beijing Institute of Technology National Engineering Laboratory for Electric Vehicles School of Mechanical Engineering Beijing100081 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Institute of artificial intelligence and robotics Xi’an Jiaotong University Xi’an710048 China

Existing methods for estimating the state of health (SOH) of lithium-ion battery (LIB) typically rely on the assumption that the distribution of noise (or outliers) in the measurement data is known. However, this assumption rarely holds true for LIB operating under real-word conditions. This article proposes a stable framework for accurate SOH estimation that accommodates noises with unknown distribution in both measurement data and label values. The framework combines generalized correntropy loss (GCL) with Savitzky-Golay (SG) filter and extreme learning machine (ELM) to obtain measurement data filter named SG-GCL and SOH estimator named generalized ELM (GELM), respectively. The SG-GCL filtering of the measurement data keeps the root mean square error (RMSE) within 0.0365%, and Pearson correlation between extracted feature and SOH improves by 0.4963, which in turn leads to the reduction of the RMSE metrics of the ELM for the estimation of the SOH by 43.69%. From the filtering results, feature extraction and estimation results proved its necessity and effectiveness. GELM effectively suppresses the influence of label value noise on the model in the training process, which reduces the SOH estimation RMSE index by more than 0.66%. The results from experiments with different distributional noise conditions show that the proposed SOH estimation framework has excellent and stable performance. © 2015 IEEE.

关键词： Mean square error

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Autonomous Multiple-Trolley Collection System with Nonholonomic Robots: Design, Control, and Implementation

arXiv

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arXiv 2024年

作者： Xie, Peijia Xia, Bingyi Hu, Anjun Zhao, Ziqi Meng, Lingxiao Sun, Zhirui Gao, Xuheng Wang, Jiankun Meng, Max Q.-H. Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Jiaxing Research Institute Southern University of Science and Technology Jiaxing China The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong The Department of Electrical and Computer Engineering The University of Alberta Canada

The intricate and multi-stage task in dynamic public spaces like luggage trolley collection in airports presents both a promising opportunity and an ongoing challenge for automated service robots. Previous research has primarily focused on handling a single trolley or individual functional components, creating a gap in providing cost-effective and efficient solutions for practical scenarios. In this paper, we propose a mobile manipulation robot incorporated with an autonomy framework for the collection and transportation of multiple trolleys that can significantly enhance operational efficiency. We address the key challenges in the trolley collection problem through the novel design of the mechanical system and the vision-based control strategy. We design a lightweight manipulator and docking mechanism, optimized for the sequential stacking and transportation of multiple trolleys. Additionally, based on the Control Lyapunov Function and Control Barrier Function, we propose a novel vision-based control with the online Quadratic Programming which significantly improves the accuracy and efficiency of the collection process. The practical application of our system is demonstrated in real-world scenarios, where it successfully executes multiple-trolley collection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming

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Tunable Rectification of Diffusion-Wave Fields by Spatiotemporal Metamaterials

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Physical Review Letters 2022年第25期129卷 256601-256601页

作者： Jiaxin Li Zhanxiang Zhang Guoqiang Xu Haoran Sun Lizhou Dai Tianlong Li Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

The diffusion process is the basis of many branches of science and engineering, and generally obeys reciprocity between two ports of a linear time-invariant medium. Recent research on classical wave dynamics has explored the spatiotemporal modulation to exhibit preferred directions in photons and plasmons. Here we report a distinct rectification effect on diffusion-wave fields by modulating the conductivity and observe nonreciprocal transport of charges. We experimentally create a spatiotemporal diffusion metamaterial, in which a mode transition to zero frequency is realized. A direct current component thereby emerges, showcasing a biased effect on the charge diffusion when the incident fundamental frequency is a multiple of the system modulation frequency. These results may find applications spanning a plethora of diffusive fields in general.

关键词： Diffusion Metamaterials Bloch-Floquet theorem

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Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment Anything

arXiv

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arXiv 2024年

作者： Wu, Zijian Schmidt, Adam Kazanzides, Peter Salcudean, Septimiu E. Robotics and Control Laboratory Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States

The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit its usage in robotically assisted surgery. Applications, such as augmented reality guidance, require little user intervention along with efficient inference to be usable clinically. In this study, we address these limitations by adopting lightweight SAM variants to meet the efficiency requirement and employing fine-tuning techniques to enhance their generalization in surgical scenes. Recent advancements in Tracking Any Point (TAP) have shown promising results in both accuracy and efficiency, particularly when points are occluded or leave the field of view. Inspired by this progress, we present a novel framework that combines an online point tracker with a lightweight SAM model that is fine-tuned for surgical instrument segmentation. Sparse points within the region of interest are tracked and used to prompt SAM throughout the video sequence, providing temporal consistency. The quantitative results surpass the state-of-the-art semi-supervised video object segmentation method XMem on the EndoVis 2015 dataset with 84.8 IoU and 91.0 Dice. Our method achieves promising performance that is comparable to XMem and transformer-based fully supervised segmentation methods on ex vivo UCL dVRK and in vivo CholecSeg8k datasets. In addition, the proposed method shows promising zero-shot generalization ability on the label-free STIR dataset. In terms of efficiency, we tested our method on a single GeForce RTX 4060/4090 GPU respectively, achieving an over 25/90 FPS inference speed. Code is available at: https://***/wuzijian1997/SIS-PT-SAM © 2024, CC BY.

关键词： Surgical equipment

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Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang Hongli Dong Yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

关键词： filtering quadratic bounds

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Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots

Graph-Based Visual-Kinematic Fusion and Monte Carlo Initiali...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： R. Khorrambakht H. Damirchi M.R. Dindarloo A. Saki S.A. Khalilpour Hamid D. Taghirad Stephan Weiss Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY School of Computer Science University of Adelaide Australia Faculty of Electrical Engineering University of Technology Tehran Iran Department of Smart Systems Technologies University of Klagenfurt Austria

Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for the kinematic parameters. This is achieved by formulating a Monte-Carlo algorithm that initializes a factor-graph representation of the calibration and localization problem. With this, we are able to jointly identify both the kinematic parameters and the visual odometry scale alongside their corresponding uncertainties. We demonstrate the practical applicability of the framework using our state-estimation dataset recorded with the ARAS-CAM suspended cable driven parallel robot, and published as part of this manuscript.

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Efficient Fault Detection in Nonlinear Industrial Process: A Reduced Kernel PCA-Based Spectral Clustering Approach

Efficient Fault Detection in Nonlinear Industrial Process: A...

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Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Khadija Attouri Majdi Mansouri Mansour Hajji Kais Bouzrara Laboratory of Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Tunisia Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The challenges posed by nonlinearities in industrial systems necessitate innovative techniques that outperform the limitations of traditional methods such as principal component analysis (PCA). While Kernel Principal Component Analysis (KPCA) offers a robust solution to handle nonlinear data, its computational requirements are a significant issue, especially for large-sized datasets. In this work, we propose a novel technique, namely, reduced kernel principal component analysis-based spectral clustering (RKPCA SpC ), to monitor and detect faults in the benchmark Tennessee Eastman process. The suggested approach addresses the complexity associated with KPCA by reducing data size during the model training phase. This reduction involves retaining only the principal components, preserving informative features, and selecting pertinent samples without compromising the original data's content. The efficacy of the proposed method is evaluated through key performance metrics, including false alarm rate (FAR), missed detection rate (MDR), detection time delay (DTD), and computation time (CT). Additionally, gained execution time (GET), gained storage space (GSP), and loss function (LF) are considered, providing a comprehensive assessment of the developed paradigms' effectiveness. The results demonstrate the promising capabilities of our proposed scheme.

关键词： Training Measurement Technological innovation Fault detection Delay effects Computational modeling Complexity theory Kernel Monitoring Principal component analysis

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Constrained Generative Sampling of 6-DoF Grasps

Constrained Generative Sampling of 6-DoF Grasps

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Jens Lundell Francesco Verdoja Tran Nguyen Le Arsalan Mousavian Dieter Fox Ville Kyrki KTH Royal Institute of Technology Sweden Department of Electrical Engineering and Automation Intelligent Robotics Group School of Electrical Engineering Aalto University Finland NVIDIA Corporation USA Paul G. Allen School of Computer Science & Engineering University of Washington Seattle USA

Most state-of-the-art data-driven grasp sampling methods propose stable and collision-free grasps uniformly on the target object. For bin-picking, executing any of those reachable grasps is sufficient. However, for completing specific tasks, such as squeezing out liquid from a bottle, we want the grasp to be on a specific part of the object's body while avoiding other locations, such as the cap. This work presents a generative grasp sampling network, VCGS, capable of constrained 6-Degrees of Freedom (DoF) grasp sampling. In addition, we also curate a new dataset designed to train and evaluate methods for constrained grasping. The new dataset, called CONG, consists of over 14 million training samples of synthetically rendered point clouds and grasps at random target areas on 2889 objects. VCGS is benchmarked against GraspNet, a state-of-the-art unconstrained grasp sampler, in simulation and on a real robot. The results demonstrate that VCGS achieves a 10-15% higher grasp success rate than the baseline while being 2–3 times as sample efficient. Supplementary material is available on our project website.

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