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Modelling of Cross Saturation Effect in Interior Permanent Magnet Synchronous Machines Using Magnetic Equivalent Circuits

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Modelling of Cross Saturation Effect in Interior Permanent M...

International Conference on Electrical Machines, ICEM

作者： D. Vuljaj Z. Hanić A. Hanić D. Žarko RIMAC AUTOMOBILI Sveta Nedelja Croatia University of Zagreb Faculty of Electrical Engineering and Computing Department of Electric Machines Drives and Automation Zagreb Croatia Geology and Petroleum Engineering University of Zagreb Faculty of Mining Croatia

This paper presents a method for calculation of flux linkages in the direct and quadrature axes of interior permanent magnet synchronous machines with a single U shaped barrier. The method is based on the magnetic equivalent circuit. For obtaining the correct results, it is essential to model the cross-saturation effect, especially for q axis current excitation due to magnetomotive force of the permanent magnets. The proposed method is fast and accurate. The paper describes modeling techniques and provides results as well as the comparisons with finite element method.

关键词： Saturation magnetization Electron tubes Magnetic circuits Magnetic flux Permanent magnets Integrated circuit modeling Equivalent circuits

Software Realization of Network Off-line Scheduling with Time-Triggered Ethernet on the Basis of Response Constraint

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Software Realization of Network Off-line Scheduling with Tim...

International Conference on Computer Science & Education (ICCSE)

作者： Qing Wang Liping Teng Yaotong Yang Huimin Wu Wenxing Hong Wenjian Li School of Electrical and Information Engineering Tianjin University Tianjin China Automation Department Xiamen University Xiamen China Tianjin Jinhang Computing Technology Research Institute Tianjin China

Time-Triggered Ethernet (TTE) is a new network communicational technic with Ethernet, which combines time service and event service. Reasonable time planning and schedule design enable three different types of traffic with various time-critical characteristics including Time-Triggered (TT) traffic, Rate-Constrained (RC) traffic and Best-Effort (BE) traffic to be transmitted regulated by their own rules and priority efficiently. This paper raises a method suited for generating TTE network off-line time schedule with response constraint. Also, this research introduces response constraint as an important consideration on the basis of existed hybrid traffic partitioning scheduling strategy. At the same time, the network schedule is used to form a composite schedule table strategy to simplify the schedule generation process. Furthermore, a software is designed to generate off-line schedule, and its rationality about generating schedule periodically is verified by practical examples.

关键词： Schedules Transmitters Task analysis Synchronization Software Receivers Real-time systems

When Deep Meets Shallow: Subspace-Based Multi-View Fusion for Instance-Level Image Retrieval

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When Deep Meets Shallow: Subspace-Based Multi-View Fusion fo...

IEEE International Conference on Robotics and Biomimetics

作者： Jun Li Bo Yang Wankou Yang Changyin Sun Hong Zhang School of Automation Southeast University Nanjing China School of Instrument Science and Engineering Southeast University Nanjinz China Department of Computing Science University of Alberta Edmonton AB Canada

ISBN: (纸本)9781728103785;9781728103778

Instance-level image retrieval, which aims to find all the images correctly matching the query instance, has attracted extensive attention in the community of computer vision and multimedia. The success of recent retrieval systems largely depends on an image signature with sufficient discriminative power for visual representation. For the past few years, massive feature learning algorithms have sprung up, and they have significantly advanced the development of instance retrieval. In particular, CNN features derived from a deep neural network allows encoding high-level image contents and demonstrates unrivaled superiority to the hand-crafted shallow image signatures. However, the shallow features still play a beneficial role in visual matching particularly when dramatic variances in viewpoint and scale are present, since they inherit certain invariance from the local robust descriptor, e.g. SIFT. Thus, it is important to leverage the complementarity between these two heterogeneous signatures for multi-view fusion in instance retrieval. Since it is still an open problem, in this paper, we propose a subspace-based multi-view fusion strategy where a shared subspace is uncovered from the original high-dimensional features yielding a compact latent representation. Since our method works in an unsupervised fashion without any training process involved, it lends itself to various real-time robotic vision tasks, e.g. place recognition and scene description. Experiments on public benchmark datasets reveal the proposed method works better than other classic fusion approaches and achieves the state-of-the-art performance.

关键词： Visualization Task analysis Robots Image retrieval Real-time systems Image representation Image reconstruction

A Study of Capsule Endoscopy Orientation Estimation Using Received Signal Strength

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A Study of Capsule Endoscopy Orientation Estimation Using Re...

International Symposium on Personal, Indoor, and Mobile Radio Communications

作者： Katjana Krhac Kamran Sayrafian Mehdi Alasti Kamya Yekeh Yazdandoost Dina Simunic Faculty of Electrical Engineering and Computing University ofZagreb Croatia Information Technology Laboratory National Institute of Standards & Technology USA AdGen Telecom Group USA Department of Electrical Engineering and Automation Aalto University Finland

ISBN: (纸本)9781538660102

Comprehensive study of wireless communication for ingestible electronics is a very challenging task. To initiate the study on wireless capsule endoscopy, an innovative immersive platform containing an enhanced 3D human body model has been developed. This platform allows for flexible placement of a capsule inside the gastrointestinal (GI) tract and multiple receivers around the abdomen area. It is shown that any directionality (or equivalently null) in the antenna radiation pattern can be exploited to sense changes in the orientation of the capsule through observation of the S21 vector at a set of on-body receivers. Two methodologies i.e. complex cross-correlation and Minkowski distance were used to assess capsule orientation estimation with respect to a reference position. The study was performed within the Ultra-Wide Band frequency range as this technology is considered to be an attractive candidate for the next generation of wireless capsule endoscopy.

关键词： Wireless Capsule Endoscopy Orientation Estimation Ultra-Wide Band Correlation Coefficient

Stabilization with a specified external gain for linear MIMO systems and its applications to control of networked systems

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arXiv 2018年

作者： Zhu, Lijun Chen, Zhiyong Chen, Xi Hill, David J. Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Electrical Engineering and Computing University of Newcastle CallaghanNSW2308 Australia Engineering Research Center of Metallurgical Automation and Measurement Technology Ministry of Education Wuhan

This paper studies a stabilization problem for linear MIMO systems subject to external perturbation that further requires the closed-loop system render a specified gain from the external perturbation to the output. The problem arises from control of networked systems, in particular, robust output synchronization of heterogeneous linear MIMO multi-agent systems via output feedback/communication. We propose a new approach that converts a class of MIMO systems into a normal form via repeated singular value decomposition and prove that a stabilization controller with a specified external gain can be explicitly constructed for the normal form. Two scenarios with static state feedback and dynamic output feedback are investigated. By integrating the reference model and internal model techniques, the robust output synchronization problem for MIMO multi-agent systems is converted into a stabilization problem with a specified external gain and solved by the developed approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Multi agent systems

A Parametric Time Frequency-Conditional Granger Causality Method Using Ultra-regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs

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arXiv 2018年

作者： Li, Yang Lei, Mengying Cui, Weigang Guo, Yuzhu Wei, Hua-Liang Department of Automation Sciences and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Advanced Innovation Center for Big Date-based Precision Medicine Beihang University Beijing China Department of Automation Sciences and Electrical Engineering Beihang University Beijing China Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3DJ United Kingdom

— Objective: This study proposes a new parametric TF (time-frequency)-CGC (conditional Granger causality) method for high-precision connectivity analysis over time and frequency in multivariate coupling nonstationary systems, and applies it to scalp and source EEG signals to reveal dynamic interaction patterns in oscillatory neocortical sensorimotor networks. Methods: The Geweke’s spectral measure is combined with the TVARX (time-varying autoregressive with exogenous input) modelling approach, which uses multiwavelets and ultra-regularized orthogonal least squares (UROLS) algorithm aided by APRESS (adjustable prediction error sum of squares), to obtain high-resolution time-varying CGC representations. The UROLS-APRESS algorithm, which adopts both the regularization technique and the ultra-least squares criterion to measure not only the signal data themselves but also the weak derivatives of them, is a novel powerful method in constructing time-varying models with good generalization performance, and can accurately track smooth and fast changing causalities. The generalized measurement based on CGC decomposition is able to eliminate indirect influences in multivariate systems. Results: The proposed method is validated on two simulations and then applied to multichannel motor imagery (MI)-EEG signals at scalp- and source-level, where the predicted distributions are well recovered with high TF precision, and the detected connectivity patterns of MI-EEG data are physiologically and anatomically interpretable and yield new insights into the dynamical organization of oscillatory cortical networks. Conclusion: Experimental results confirm the effectiveness of the proposed TF-CGC method in tracking rapidly varying causalities of EEG-based oscillatory networks. Significance: The novel TF-CGC method is expected to provide important information of neural mechanisms of perception and cognition. Copyright © 2018, The Authors. All rights reserved.

关键词： Statistical tests

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

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arXiv 2021年

作者： Hering, Alessa Hansen, Lasse Mok, Tony C.W. Chung, Albert C.S. Siebert, Hanna Häger, Stephanie Lange, Annkristin Kuckertz, Sven Heldmann, Stefan Shao, Wei Vesal, Sulaiman Rusu, Mirabela Sonn, Geoffrey Estienne, Théo Vakalopoulou, Maria Han, Luyi Huang, Yunzhi Yap, Pew-Thian Brudfors, Mikael Balbastre, Yaël Joutard, Samuel Modat, Marc Lifshitz, Gal Raviv, Dan Lv, Jinxin Li, Qiang Jaouen, Vincent Visvikis, Dimitris Fourcade, Constance Rubeaux, Mathieu Pan, Wentao Xu, Zhe Jian, Bailiang De Benetti, Francesca Wodzinski, Marek Gunnarsson, Niklas Sjölund, Jens Grzech, Daniel Qiu, Huaqi Li, Zeju Thorley, Alexander Duan, Jinming Großbröhmer, Christoph Hoopes, Andrew Reinertsen, Ingerid Xiao, Yiming Landman, Bennett Huo, Yuankai Murphy, Keelin Lessmann, Nikolas van Ginneken, Bram Dalca, Adrian V. Heinrich, Mattias P. Institute of Medical Informatics Universität zu Lübeck Ratzeburger Allee 160 Lübeck23562 Germany Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany Department of Radiology and Nuclear Medicine Radboud University Medical Center GA Nijmegen6525 Netherlands The Institute of Medical Informatics Universität zu Lübeck Lübeck23562 Germany The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong The Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany The Department of Radiology Stanford University StanfordCA94305 United States The Department of Urology Stanford University StanfordCA94305 United States The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette 91190 France Université Paris-Saclay Institut Gustave Roussy Inserm Radiothérapie Moléculaire et Innovation Thérapeutique Villejuif94800 France The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette91190 France The Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen6525 GA Netherlands The School of Automation Nanjing University of Information Science and Technology Nanjing210044 China The School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom The Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital United States Harvard Medical School Boston United States The King’s College London United Kingdom The Tel Aviv University The Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology Hubei Wuhan430074 China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Sci

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration data set for comprehensive characterisation of deformable registration algorithms. A continuous evaluation will be possible at https://***. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. We established an easily accessible framework for training and validation of 3D registration methods, which enabled the compilation of results of over 65 individual method submissions from more than 20 unique teams. We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. This paper describes datasets, tasks, evaluation methods and results of the challenge, as well as results of further analysis of transferability to new datasets, the importance of label supervision, and resulting bias. While no single approach worked best across all tasks, many methodological aspects could be identified that push the performance of medical image registration to new state-of-the-art performance. Furthermore, we demystified the common belief that conventional registration methods have to be much slower than deep-learning-based methods. © 2021, CC BY.

关键词： Image registration

Composite Learning for Trajectory Tracking Control of Robot Manipulators with Output Constraints

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Composite Learning for Trajectory Tracking Control of Robot ...

International Conference on Information Science and Technology (ICIST)

作者： Dianye Huang Chenguang Yang Yongping Pan Shilu Dai Zhaojie Ju Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Biomedical Engineering National University of Singapore Singapore Singapore School of Computing University of Portsmouth Portsmouth UK

In this paper, a trajectory tracking scheme for robot manipulators with unknown dynamics is investigated, with the consideration of output constraints as well as small bounded external disturbances. Firstly, a modified backstepping control scheme is employed to control the robot manipulators where in the first step of the design a tan-type barrier Lyapunov candidate is chosen in order to tackle the constraint problem. Secondly, the philosophy of dynamic surface control is incorporated to implement the calculation of prediction errors, which can also reduce “explosion of complexity” of the backstepping scheme. In addition, composite learning is introduced for a better estimation of unknown parameters, and for canceling out the uncertainties of the robot manipulators. Stability analysis shows that the proposed control scheme guarantees a small bounded tracking error with parameter convergence in the absence of the stringent persistent excitation condition. Finally, a simulation is conducted and the results demonstrate the superiority of the proposed controller in the aspects of tracking capability and parameter estimation.

关键词： Manipulator dynamics Backstepping Uncertainty Control systems Convergence

An input-delay method for event-triggered control of nonlinear systems

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arXiv 2018年

作者： Zhu, Lijun Chen, Zhiyong Hill, David J. Du, Shengli Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Electrical Engineering and Computing University of Newcastle CallaghanNSW2308 Australia College of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China

The paper proposes a novel event-triggered control scheme for nonlinear systems based on the input-delay method. Specifically, the closed-loop system is associated with a pair of auxiliary input and output. The auxiliary output is defined as the derivative of the continuous-time input function, while the auxiliary input is defined as the input disturbance caused by the sampling or equivalently the integral of the auxiliary output over the sampling period. As a result, it forms a cyclic mapping from the input to the output via the system dynamics and back from the output to the input via the integral. The event-triggering law is constructed to make the mapping contractive such that the stabilization is achieved and an easy-to-check Zeno-free condition is provided. Within this framework, we develop a theorem for the event-triggered control of interconnected nonlinear systems which is employed to solve the event-triggered control for lower-triangular systems with dynamic uncertainties. Copyright © 2018, The Authors. All rights reserved.

关键词： Nonlinear systems