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Research Square 2021年

作者： Niu, Jiaojiao Chen, Degang Ma, Yinglong Li, Jinhai North China Electric Power University Beijing Campus China Kunming University of Science and Technology Lianhua Campus China School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Mathematics and Physics North China Electric Power University Beijing102206 China Data Science Research Center Kunming University of Science and Technology Yunnan Kunming650500 China

Knowledge graph embedding (KGE) are routinely used to represent entities and their relations in knowledge bases with a quantitative measure, and the triples usually play the role of basic units in KGE learning. Considering that triples are sometimes far from adequate and knowledge graph itself contains a lot of information, this paper employs FCA-based technology to mine the deterministic knowledge from knowledge graph, that is, the formal concept, and attempts to establish the relationship between knowledge graph (KG) and formal concept analysis (FCA). Specifically, each set of triples sharing the same head entity are grouped as a graph granule and the concepts of each graph granule are mined. By further exploration, the maximal concepts are integrated into embedding learning to develop a novel KGE model named TransGr for knowledge graph completion. This model learns a matrix for each maximal concept in graph granule as well as a vector for each entity and relation. The performed experiments on link prediction and triple classification tasks demonstrate that the proposed TransGr model is effective on the datasets with relatively complete graph granules. © 2021, CC BY.

关键词： Formal concept analysis

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Resource allocation for millimeter-wave train-ground communications in high-speed railway scenarios

arXiv

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arXiv 2021年

作者： Zhang, Xiangfei Niu, Yong Mao, Shiwen Cai, Yunlong He, Ruisi Ai, Bo Zhong, Zhangdui Liu, Yiru State Key Laboratory of Rail Traffic Control and Safety Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China National Mobile Communications Research Laboratory Southeast University Nanjing211189 China Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Department of ISEE Zhejiang University China State Key Laboratory of Rail Traffic Control and Safety Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China

With the development of wireless communication, higher requirements arise for train-ground wireless communications in high-speed railway (HSR) scenarios. The millimeter-wave (mm-wave) frequency band with rich spectrum resources can provide users in HSR scenarios with high performance broadband multimedia services, while the full-duplex (FD) technology has become mature. In this paper, we study train-ground communication system performance in HSR scenarios with mobile relays (MRs) mounted on rooftop of train and operating in the FD mode. We formulate a nonlinear programming problem to maximize network capacity by allocation of spectrum resources. Then, we develop a sequential quadratic programming (SQP) algorithm based on the Lagrange function to solve the bandwidth allocation optimization problem for track-side base station (BS) and MRs in this mm-wave train-ground communication system. Extensive simulation results demonstrate that the proposed SQP algorithm can effectively achieve high network capacity for train-ground communication in HSR scenarios while being robust to the residual self-interference (SI). Copyright © 2021, The Authors. All rights reserved.

关键词： Resource allocation

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Research on H∞ Preview control Algorithm for Industrial Wireless Sensor Networks

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Journal of Physics: Conference Series 2021年第1期2025卷

作者： Yuanbo Shi Yueyang Huang Shaojing Hou Yinghao Wu School of Computer and Communication Engineering Liaoning Petrochemical University Fushun 113001 Liaoning China School of Information and Control Engineering Liaoning Petrochemical University Fushun 113001 Liaoning China

In order to solve the problem of wireless sensor network control system with network delay and packet loss, a H∞ preview control algorithm is designed. Firstly, the wireless sensor network model with delay and packet loss is established, and the system error and predictable target signal are introduced to construct the extended error system. Secondly, the state feedback controller with memory is designed. By constructing Lyapunov function and linear matrix inequality, the design method of H∞ controller and the sufficient conditions for the stability of the system are derived. The optimal H∞ preview controller algorithm is obtained by solving the LMI optimization problem. Finally, the effectiveness of H∞ preview controller algorithm is verified by simulation.

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Gram Matrix Based Transistor Open-Circuit Fault Diagnosis Method for Voltage-Source Inverter Fed Vector controlled Induction Motor Drives

Gram Matrix Based Transistor Open-Circuit Fault Diagnosis Me...

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International Conference on Power Electronics and Motion control (IPEMC)

作者： Yang Zhou Feng Wu Jin Zhao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Imaging Processing and Intelligence Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering Nanyang Technological University

ISBN: (数字)9781728153018

ISBN: (纸本)9781728153025

This paper proposed a novel, real-time and high efficiency diagnostic method for Insulated Gate Bipolar Transistor(IGBT) open-circuit fault in pulse-width-modulated (PWM) voltage- source inverter fed vector-controlled induction motor. Similarity among three phase currents of inverter can be used to detect transistor open-circuit faults according to the topological analysis of inverter operations both in healthy and failure condition. In this paper, Gram-matrix of three phase currents is proposed to extract features, the eigenvalues of the matrix are proposed to measure the similarity and diagnose transistor open-circuit fault. The proposed method is fast and fair-robust, both single and multiple faults on the same leg can be effectively detected and located. Experimental results evaluate efficiency and merits of proposed diagnostic method.

关键词： Fault diagnosis Voltage source inverters Feature extraction Real-time systems Eigenvalues and eigenfunctions Transistors Voltage control

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Adaptive Neural Prescribed Performance DSC for Non-affine SISO Nonlinear Systems with External Disturbances

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IFAC-PapersOnLine 2018年第15期51卷 748-753页

作者： Tooranjipour, Pouria Vatankhah, Ramin Arefi, Mohammad Mehdi Montazeri, Allahyar School of Mechanical Engineering Shiraz University Shiraz Iran Department of Power and Control Engineering School of Electrical and Computer Engineering Shiraz University Shiraz Iran Engineering Department Lancaster University Lancaster United Kingdom

Explosion of complexity and undesirable transient response of systems, are two major problems that conventional backstepping methods suffer from it. Furthermore, lack of information about the system and undesirable external disturbances are other problems that have been addressed in this paper. Therefore, an adaptive neural controller is designed to consider the proposed problems in this paper. The presented controller is constructed for the class of single-input, single-output (SISO) non-affine strict feedback systems with unknown gain signs and a neural network is employed to approximate unknown functions. By applying dynamic surface control (DSC) and prescribed performance functions, two major problems of an explosion in terms and the transient response of the system will be solved, respectively. Nussbaum functions are also utilized to address the problem of unknown gain signs. The proposed controller guarantees that all the closed-loop signals are semi-globally, uniformly ultimately bounded (SGUUB). Finally, in order to show the feasibility of this approach, a simulation example is provided. © 2018

关键词： Adaptive control systems Backstepping controllers Feedback control Transient analysis Dynamic surface control Neuro adaptive control Non affine nonlinear systems Nussbaum type functions Prescribed performance

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FES based wrist tremor suppression using multi-periodic repetitive control ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10135-10140页

作者： Zan Zhang Bing Chu Yanhong Liu D.H. Owens School of Electrical Engineering Zhengzhou University Zhengzhou China Department of Electronics and Computer Science university of southampton Southampton SO17 1BJ UK Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK

Tremor is a very common motor disorder, mainly manifested as involuntary, periodic and rhythmic movement in any part of the body, especially in hands and upper-limbs, which seriously affects the life quality of patients. Functional electrical stimulation (FES) has been shown a promising technique to suppress tremor. Most existing FES based design methods assume tremor is a single frequency signal which however is a highly idealized simplification of the real case which contains multiple-frequency or even a frequency band, therefore limiting their practical performance. To address this problem, this paper proposes a controller design method based on multi-periodic repetitive control that is capable of suppressing tremor signal with multiple frequencies. Simulation and experimental results verify the effectiveness of the proposed method.

关键词： Functional electrical stimulation (FES) tremor suppression multi-periodic repetitive control simulation experimental verification

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Composite Error-based Prescribed Performance control with Unknown Initial Error for Multiple Trains Cooperation

Composite Error-based Prescribed Performance Control with Un...

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Chinese control and Decision Conference, CCDC

作者： Dingyi Ma Shijie Zhou Shigen Gao School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper presents a new composite error-based prescribed performance control (CEB-PPC) method for multiple trains cooperation with model uncertainties. A new prescribed performance function, which is capable of relaxing the requirements of known initial error and bringing in a large-enough initially allowable ranges, is introduced. The key idea of CEB-PPC is the utilization of summation of "transformed" and "true" tracking error variables in proposed controllers. Our method also features with the ultimate boundaries are characterized by control gain and prescribed performance function (PPF) simultaneously, while only PPF in the traditional PPC methodology. Simulation results are given to demonstrate the effectiveness of proposed method in controlling cooperation of three trains.

关键词： Simulation Trajectory Transient analysis Convergence State feedback Public transportation Information technology

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A Novel Power Weighted Multipath Component Clustering Algorithm Based on Spectral Clustering

A Novel Power Weighted Multipath Component Clustering Algori...

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IEEE Conference on Vehicular Technology (VTC)

作者： Mingtao Hu Yuxin Ye Ruisi He Bo Ai Chen Huang Zhangdui Zhong School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China

ISBN: (数字)9781728152073

ISBN: (纸本)9781728140537

In the real propagation environments, multipath components (MPCs) in wireless channel usually exist as clusters. Cluster based structure of MPCs has been widely used in wireless channel modeling. In this paper, a novel MPC clustering algorithm is proposed based on spectral clustering. Considering that MPCs having strong power should usually be grouped into different clusters, the algorithm introduces a power-weighted processing to identify the similarity of each MPC. The process of weighting the power is conducted by generating similarity matrix using the full link method of Gaussian kernel function in the traditional spectral clustering algorithm. In order to achieve high clustering accuracy, the dimensionality reduction method of Laplacian Eigenmap is decomposed by using the normalized cut method, the obtained eigenvectors are re-clustered to cut the generated similarity matrix for MPC clustering. In the simulation results, it is found that this algorithm can well separate MPCs with high powers into different clusters and achieves better clustering performance compared with KPowerMeans, Kmeans, and the traditional spectral clustering algorithms.

关键词： Clustering algorithms Delays Machine learning algorithms Wireless communication Predictive models Shape Matrix decomposition

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Energy-Aware Dynamic Computation Offloading in High-Speed Railway Networks with D-TDD

Energy-Aware Dynamic Computation Offloading in High-Speed Ra...

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IEEE Conference on Vehicular Technology (VTC)

作者： Qi Zhang Haina Zheng Zhangdui Zhong School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China

ISBN: (数字)9781728194844

ISBN: (纸本)9781728194851

This paper investigates the energy-aware dynamic resource allocation and computation offloading in high-speed railway networks with dynamic time division duplex (D-TDD), where all tasks of passengers in the high-mobility train are aggregated to be a "big task", and the vehicle server (VS) deployed on the train completes the "big task" by two processing modes, i.e., local computing and vehicular edge offloading. For such a system, an optimization problem is formulated to minimize the energy consumption by jointly optimizing the size of task block, the offloading ratio, the transmit power and the central processing unit (CPU) speed of VS with multiple system constraints. As the problem is non-convex with unknown solution, a bi-level optimization method is proposed to solve it. Via one-dimensional searching and Lagrangian multiplier method, the global optimal solution is obtained with high computational complexity. Then, a suboptimal approach is proposed with low computational complexity. Numerical results show that the performance of our proposed scheme significantly outperforms some other benchmark schemes, and a great performance gain is obtained via employing D-TDD. Besides, the effect of Doppler shift on the system performance is also discussed.

关键词： System performance Dynamic scheduling Rail transportation Central Processing Unit Task analysis Vehicle dynamics Computational complexity

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Statistical approach to detection of attacks for stochastic cyber-physical systems

arXiv

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arXiv 2020年

作者： Marelli, Damián Sui, Tianju Fu, Minyue Lu, Renquan School of Automation Guangdong University of Technology Guangzhou China French Argentine International Center for Information and Systems Sciences National Scientific and Technical Research Council Argentina School of Control Science and Engineering Dalian University of Technology Dalian China School of Electrical Engineering and Computer Science University of Newcastle CallaghanNSW2308 Australia School of Automation Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guandong University of Technology Guangzhou China

We study the problem of detecting an attack on a stochastic cyber-physical system. We aim to treat the problem in its most general form. We start by introducing the notion of asymptotically detectable attacks, as those attacks introducing changes to the system’s output statistics which persist asymptotically. We then provide a necessary and sufficient condition for asymptotic detectability. This condition preserves generality as it holds under no restrictive assumption on the system and attacking scheme. To show the importance of this condition, we apply it to detect certain attacking schemes which are undetectable using simple statistics. Our necessary and sufficient condition naturally leads to an algorithm which gives a confidence level for attack detection. We present simulation results to illustrate the performance of this algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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