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Remaining Useful Battery Life Prediction for UAVs based on Machine Learning

IFAC-PapersOnLine 2017年第1期50卷 4727-4732页

作者： Mansouri S.S. Karvelis P. Georgoulas G. Nikolakopoulos G. Robotics Group Control Engineering Division of the Department of Computer Electrical and Space Engineering Luleå University of Technology Luleå SE-97187 Sweden Laboratory of Knowledge and Intelligent Computing Department of Computer Engineering Technological Educational Institute of Epirus Arta Greece

Unmanned Aerial Vehicles are becoming part of many industrial applications. The advancements in battery technologies played a crucial part for this trend. However, no matter what the advancements are, all batteries have a fixed capacity and after some time drain out. In order to extend the flying time window, the prediction of the time that the battery will no longer be able to support a flying condition is crucial. This in fact can be cast as a standard Remaining Useful Life prognostic problem, similarly encountered in many fields. In this article, the problem of Remaining Useful Life estimation of a battery, under different flight conditions, is tackled using four machine learning techniques: a linear sparse model, a variant of support vector regression, a multilayer perceptron and an advanced tree based algorithm. The efficiency of the overall proposed machine learning techniques, in the field of batteries prognostics, is evaluated based on multiple experimental data from different flight conditions. © 2017

关键词： Battery Machine Learning Prediction Remaining Useful Life UAVs

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Generalized dynamics in social networks with antagonistic interactions

arXiv

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arXiv 2018年

作者： Zhai, Shidong Zheng, Wei Xing Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China School of Computing Engineering and Mathematics Western Sydney University SydneyNSW2751 Australia

In this paper, we investigate a general nonlinear model of opinion dynamics in which both state-dependent susceptibility to persuasion and antagonistic interactions are considered. According to the existing literature and socio-psychological theories, we examine three specializations of state-dependent susceptibility, that is, stubborn positives scenario, stubborn neutrals scenario, and stubborn extremists scenario. Interactions among agents form a signed graph, in which positive and negative edges represent friendly and antagonistic interactions, respectively. Based on Perron-Frobenius property of eventually positive matrices and LaSalle invariance principle, we conduct a comprehensive theoretical analysis of the generalized nonlinear opinion dynamics. We obtain some sufficient conditions such that the states of all agents converge into the subspace spanned by the right positive eigenvector of an eventually positive matrix. When there exists at least one entry of the right positive eigenvector which is not equal to one, the derived results can be used to describe different levels of an opinion. Finally, we present two examples to demonstrate the effectiveness of the theoretical findings. Copyright © 2018, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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CONTINUITY-DISCRIMINATION CONVOLUTIONAL NEURAL NETWORK FOR VISUAL OBJECT TRACKING

CONTINUITY-DISCRIMINATION CONVOLUTIONAL NEURAL NETWORK FOR V...

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IEEE International Conference on Multimedia and Expo

作者： Shen Li Bingpeng Ma Hong Chang Shiguang Shan Xilin Chen Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Bejing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China

This paper proposes a novel model, named Continuity-Discrimination Convolutional Neural Network (CD-CNN), for visual object tracking. Existing state-of-the-art tracking methods do not deal with temporal relationship in video sequences, which leads to imperfect feature representations. To address this problem, CD-CNN models temporal appearance continuity based on the idea of temporal slowness. Mathematically, we prove that, by introducing temporal appearance continuity into tracking, the upper bound of target appearance representation error can be sufficiently small with high probability. Further, in order to alleviate inaccurate target localization and drifting, we propose a novel notion, object-centroid, to characterize not only objectness but also the relative position of the target within a given patch. Both temporal appearance continuity and object-centroid are jointly learned during offline training and then transferred for online tracking. We evaluate our tracker through extensive experiments on two challenging benchmarks and show its competitive tracking performance compared with state-of-the-art trackers.

关键词： Visual object tracking Temporal appearance continuity Object-centroid discrimination

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A performance analysis of computing the LU and the QR matrix decompositions on the CPU and the GPU

A performance analysis of computing the LU and the QR matrix...

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作者： Gajić, Dušan B. Stanković, Radomir S. Radmanović, Miloš Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Department of Computer Science Faculty of Electronic Engineering University of Niš Niš Serbia

We present an analysis of time efficiency of five different implementations of the LU and the QR decomposition of matrices performed on central processing unit (CPUs) and graphics processing units (GPUs). Three of the considered implementations, developed using the Eigen C++ library, Intel MKL, and MATLAB are executed on a multi-core CPU. The remaining two implementations are processed on a GPU and employ MATLAB's Parallel computing Toolbox and Nvidia CUDA augmented with the cuSolver library. Computation times are compared using randomly generated single- and double-precision floating-point matrices. The experiments for the LU decomposition show that the two GPU implementations offer best performance for matrices that can fit into the GPU global memory. For larger LU decomposition problem instances, Intel MKL on the CPU is found to be the fastest approach. Furthermore, Intel MKL also proves to be the fastest method for computing QR decomposition for all considered sizes of matrices. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： MATLAB

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Max-min fairness user scheduling and power allocation in full-duplex OFDMA systems

arXiv

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arXiv 2018年

作者： Zhang, Xiaozhou Chang, Tsung-Hui Liu, Ya-Feng Shen, Chao Zhu, Gang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In a full-duplex (FD) multi-user network, the system performance is not only limited by the self-interference but also by the co-channel interference due to the simultaneous uplink and downlink transmissions. Joint design of the uplink/downlink transmission direction of users and the power allocation is crucial for achieving high system performance in the FD multi-user network. In this paper, we investigate the joint uplink/downlink transmission direction assignment (TDA), user paring (UP) and power allocation problem for maximizing the system max-min fairness (MMF) rate in a FD multi-user orthogonal frequency division multiple access (OFDMA) system. The problem is formulated with a two-time-scale structure where the TDA and the UP variables are for optimizing a long-term MMF rate while the power allocation is for optimizing an instantaneous MMF rate during each channel coherence interval. We show that the studied joint MMF rate maximization problem is NP-hard in general. To obtain high-quality suboptimal solutions, we propose efficient methods based on simple relaxation and greedy rounding techniques. Simulation results are presented to show that the proposed algorithms are effective and achieve higher MMF rates than the existing heuristic methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Optimization

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Siamese-ResNet: Implementing Loop Closure Detection based on Siamese Network

Siamese-ResNet: Implementing Loop Closure Detection based on...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Qiu, Kai Ai, Yunfeng Tian, Bin Wang, Bin Cao, Dongpu School of Aritificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China School of Software Engineering University of Science and Technology of China HeFei230026 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada

ISBN: (纸本)9781538644522

Deep learning has made significant breakthroughs in the tasks of image classification, detection, segmentation, etc. However, the application of deep learning in robotics is still scarce. SLAM is a fundamental problem in robotics and loop closure detection is an important part of SLAM. This paper attempts to use supervised learning methods to solve the loop closure detection problem in vision SLAM. We proposed Siamese-ResNet network, which combines Siamese network with ResNet to detect loop closure. To show the effectiveness of Siamese-ResNet, we evaluate Siamese-ResNet and FabMap2.0 on several open published datasets, like TUM SLAM dataset and FabMap SLAM dataset. Compared with FabMap2.0, Siamese-ResNet shows higher accuracy, better robustness and shorter time-consuming. © 2018 IEEE.

关键词： Robotics

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Lom： Discovering Logic Flaws Within MongoDB-based Web Applications

引用

International Journal of Automation and computing 2017年第1期14卷 106-118页

作者： Shuo Wen Yuan Xue Jing Xu Li-Ying Yuan Wen-Li Song Hong-Ji Yang Guan-Nan Si Institute of Machine Intelligence College of Computer and Control Engineering Nankai University Tianjin 300350 China Department of Electrical Engineering and Computer Science Vanderbilt University Nashville Tennessee 37212 USA Centre for Creative Computing Bath Spa University Bath BA2 9BN UK School of Information Science and Electrical Engineering Shandong Jiaotong University Ji'nan 250357 China

Logic flaws within web applications will allow malicious operations to be triggered towards back-end database. Existing approaches to identifying logic flaws of database accesses are strongly tied to structured query language （SQL） statement construction and cannot be applied to the new generation of web applications that use not only structured query language （NoSQL） databases as the storage tier. In this paper, we present Lom, a black-box approach for discovering many categories of logic flaws within MongoDB- based web applications. Our approach introduces a MongoDB operation model to support new features of MongoDB and models the application logic as a mealy finite state machine. During the testing phase, test inputs which emulate state violation attacks are constructed for identifying logic flaws at each application state. We apply Lom to several MongoDB-based web applications and demonstrate its effectiveness.

关键词： Logic flaw web application security not only structured query language （NoSQL） database black-box MougoDB.

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Reliable Shortest Path Guidance in Stochastic Road Networks Using Convolution-Based Path Finding Algorithm 18

Reliable Shortest Path Guidance in Stochastic Road Networks ...

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18th COTA International Conference of Transportation Professionals: Intelligence, Connectivity, and Mobility, CICTP 2018

作者： Chen, Peng Tong, Rui Lu, Guangquan Wang, Yunpeng Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang Univ. Xue Yuan Rd. No. 37 Hai Dian District Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Xue Yuan Rd. No. 37 Hai Dian District Beijing100191 China

ISBN: (数字)9780784481523

ISBN: (纸本)9780784481523

Most existing research on routing guidance only pays attention to the average value of path travel time, which fails to consider travel time variability (TTV) and travel time reliability preferences by different travelers. In this study, a convolution-based modified genetic algorithm (CMGA) is proposed to find the reliable shortest path in stochastic road networks. By accounting for traveler risk tolerance, the algorithm enables the provision of personalized routing guidance for individual travelers. To support online applications in a large-scale network, reasonable heuristic constraints are imposed to help reduce the computational workload and accelerate the convergence speed of the search process. Numerical case studies based on a grid network with random offsets are provided, and the results help verify that the algorithm has the potential to solve reliable shortest path searching problems in a large-scale network with desirable efficiency. © 2018 American Society of Civil Engineers.

关键词： Convolution

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Estimation of Non-integer Order Models to Represent the Pressure Dynamics in Common-rail Natural Gas Engines

引用

IFAC-PapersOnLine 2017年第1期50卷 14551-14556页

作者： Kapetina, Mirna Lino, Paolo Maione, Guido Rapai, Milan University of Novi Sad Faculty of Technical Sciences Computing and Control Department Trg D. Obradovica 6 Novi Sad Serbia Politecnico di Bari Department of Electrical and Information Engineering Via E. Orabona 4 Bari Italy

Automotive natural gas engines are designed to dramatically reduce the emission of polluting gases, particulate matter, and harmful substances associated to combustion of Diesel or gasoline fuels. Their performance depends on the accurate metering of the air/fuel ratio, which is pursued by controlling the gas injection timing and the pressure in the common rail volume. To this aim, an accurate control-oriented model is necessary to represent gas pressure dynamics in the main parts of the injection system. This work focuses on the gas transition from inner parts of the system to the common rail. The aim is to identify a linear non-integer-order model that describes the process in a more effective and compact way than ARX integer-order models of high order. Identification is performed in a non-parametric setting, trying to identify the optimal smooth fit in the frequency domain by minimization of an appropriate discrepancy criterion, between the actual measurements and the model outputs. In this way, the model structure will be obtained as part of the identification process and will not be fixed a priori. © 2017

关键词： Compressed natural gas Diesel engines Frequency response Gas engines Gases Particle swarm optimization (PSO) Actual measurements control oriented models Fractional order systems Harmful substances Identification process Injection systems Model identification Particulate Matter

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Introduction

Advances in Industrial Control

引用

Advances in Industrial control 2018年第9783319610207期 1-18页

作者： Orsag, Matko Korpela, Christopher Oh, Paul Bogdan, Stjepan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Department of Electrical Engineering and Computer Science United States Military Academy West PointNY United States Department of Mechanical Engineering University of Nevada Las Vegas Las VegasNV United States

Aerial robotics has reached significant maturity in the last few years. Thus, the number of new unmanned aerial vehicles (UAV) and unmanned aerial systems (UAS), applications, and companies producing them has increased in a very important way. The number of publications and presentations in conferences has also experienced a large increase. Moreover, almost every day we can find articles, videos, and news in the general media related to drones. © Springer International Publishing AG 2018.

关键词： Antennas

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