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第37届中国控制会议

作者： Shuhuan Wen Jianhua Chen Zhen Li Ahmad B.Rad Kamal Mohammed Othman the Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University the school of Engineering Sciences Simon Fraser University

This paper proposes a fuzzy Q-learning(FQL)algorithm to solve the problem of the robot obstacle avoidance in unknown *** algorithm is used to localize the position of the *** Q-learning algorithm,optimized Q-learning algorithm,FQL algorithm are *** simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective.

关键词： FASTSLAM fuzzy logic control path planning obstacle avoidance Q-learning

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Coverage Probability-Constrained Maximum Throughput in UAV-Aided SWIPT Networks

Coverage Probability-Constrained Maximum Throughput in UAV-A...

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IEEE International Conference on Communications Workshops, ICC

作者： Ruihong Jiang Ke Xiong Tong Liu Duohua Wang Zhangdui Zhong School of Computer and Information Technology Beijing Jiaotong University Beijing China Beijing Computing Center Beijing China ZTE Corporation Xi'an China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

This paper investigates the coverage provability-constrained throughput in unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) networks, where UAVs are used as aerial base stations and their positions are modeled by the 2-dimension Poisson point process (2-D PPP). The ground users (GUs) decode information as well as harvest energy from the transmitted signals from UAVs. Both power splitting (PS) and time switching (TS) architectures are employed at GUs. By using a stochastic geometry approach, the explicit expressions of the information-energy (I-E) coverage probabilities are derived. To describe the optimal deployment density of UAVs, an optimization problem is formulated to maximize the system throughput subject to the I-E coverage probability constraint. By using Karush-Kuhn-Tucker (KKT) conditions, the closed-form solution is derived. Simulation results demonstrate the correctness of our derived analytical results and show that compared with traditional linear EH model, the nonlinear EH model yields significant difference performance behaviors of the system. Moreover, the nonlinear EH model has a greater impact on EH for the system with TS-enabled GU than that with PS-enabled one. With the increment of the outage threshold, the required density of UAVs should be increased and both the throughput and the energy first increase and then decrease.

关键词： Throughput Wireless communication Unmanned aerial vehicles Wireless sensor networks Integrated circuit modeling Analytical models Fading channels

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Safety monitoring in construction site based on unmanned aerial vehicle platform with computer vision using transfer learning techniques 7

Safety monitoring in construction site based on unmanned aer...

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7th Asia-Pacific Workshop on Structural Health Monitoring, APWSHM 2018

作者： Guo, Yapeng Niu, Haowei Li, Shunlong Harbin Institute of Technology School of Transportation Science and Engineering Harbin China Key Lab of Intelligent Disaster Mitigation Ministry of Industrial and Information Technology Harbin China Key Lab of Structures Dynamic Behaviour and Control Ministry of Education Harbin China

ISBN: (纸本)9783000603594

Safety is an inevitable issue in all kinds of construction sites. The most effective way to insure human's safety is wearing safety helmet, thus whether wearing or not is a main problem of safety monitoring. This paper proposed an approach using deep learning-based computer vision techniques to detect workers (i.e., not wearing safety helmet) from image sequences shot by unmanned aerial vehicle (UAV). Firstly training and testing dataset were created using label tools as a size of 300×300. Then a fine-tune method based on single shot multibox detector network was employed to get high accuracy of detection. The effectiveness and accuracy of methods were validated and discussed. Finally, some visualization work has been done for a deeper understanding of the network. © APWSHM 2018. All rights reserved.

关键词： computer vision

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A Learning Evasive Email-Based P2P-Like Botnet

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China Communications 2018年第2期15卷 15-24页

作者： Zhi Wang Meilin Qin Mengqi Chen Chunfu Jia Yong Ma College of Computer and Control Engineering Nankai University Tianjin 300350 China Information Security Evaluation Center of Civil Aviation Civil Aviation University of China Tianjin 300300 China Key Lab. on High Trusted Information System in Hebei Province Baoding 071002 China

Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution. But the real-world malware data distribution is not stable and changes with time. By exploiting the knowledge of the machine learning algorithm and malware data concept drift problem, we show a novel learning evasive botnet architecture and a stealthy and secure C&C mechanism. Based on the email communication channel, we construct a stealthy email-based P2 P-like botnet that exploit the excellent reputation of email servers and a huge amount of benign email communication in the same channel. The experiment results show horizontal correlation learning algorithm is difficult to separate malicious email traffic from normal email traffic based on the volume features and time-related features with enough confidence. We discuss the malware data concept drift and possible defense strategies.

关键词： malware botnet learning evasion command and control

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Guidance Vector Field Encoding based on Contraction Analysis 16

Guidance Vector Field Encoding based on Contraction Analysis

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16th European control Conference, ECC 2018

作者： Wu, Chengshuai Chen, Jian Jeltsema, DImitri Dai, And Chenxi State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Section Control Systems Engineering HAN University of Applied Science P.O. Box 2217 Arnhem6802 CE Netherlands Department of Electrical and Computer Engineering Ohio State University Columbus43210 United States

ISBN: (纸本)9783952426982

The guidance vector field encoding problem is revisited via exploiting the recently developed differential Lyapunov framework for contraction analysis. In control applications, a designed guidance vector field is utilized to guide a particle (such as a robot, or an end actuator) to converge to and circulate along a target curve, such as robot navigation, or motion planing. This paper proposes some new methods for guidance vector filed encoding. The methods analyze the guidance vector field encoding problem from a theoretical perspective providing insights into the problem, and it shows that the contraction analysis is a natural theoretical tool for guidance vector encoding. Furthermore, the differences and relations between the proposed result and the previous methods are discussed. Simulation examples are presented to illustrate the effectiveness of the proposed methods. © 2018 European control Association (EUCA).

关键词： Robots

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Analysis of moving target defense against false data injection attacks on power grid

arXiv

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arXiv 2019年

作者： Zhang, Zhenyong Deng, Ruilong Yau, David K.Y. Cheng, Peng Chen, Jiming State Key Laboratory of Industrial Control Technology College of Control Science and Engi-neering Zhejiang University Hangzhou310027 China School of Computer Science and Engineering Nanyang Technological University 639798 Singapore Information Systems Technology and Design Singapore University of Technology and Design 487372 Singapore

Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker to launch stealthy FDI attacks generated with former branch susceptances. In this paper, we prove that, an MTD has the capability to thwart all FDI attacks constructed with former branch susceptances only if (i) the number of branches l in the power system is not less than twice that of the system states n (i.e., l ≥ 2n, where n + 1 is the number of buses);(ii) the susceptances of more than n branches, which cover all buses, are perturbed. Moreover, we prove that the state variable of a bus that is only connected by a single branch (no matter it is perturbed or not) can always be modified by the attacker. Nevertheless, in order to reduce the attack opportunities of potential attackers, we first exploit the impact of the susceptance perturbation magnitude on the dimension of the stealthy attack space, in which the attack vector is constructed with former branch susceptances. Then, we propose that, by perturbing an appropriate set of branches, we can minimize the dimension of the stealthy attack space and maximize the number of covered buses. Besides, we consider the increasing operation cost caused by the activation of MTD. Finally, we conduct extensive simulations to illustrate our findings with IEEE standard test power systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Network security

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Sensor Fault Detection of Continuous Casting Mold Vibration System Driven by Servo Motor

Sensor Fault Detection of Continuous Casting Mold Vibration ...

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第37届中国控制会议

作者： Xia Wu Jianxiong Li Yiming Fang Zhiqiang Wang Key Lab of Industrial Computer Control Engineering of Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

The problem of sensor fault diagnosis and reconstruction of the continuous casting mold vibration displacement system driven by servo motor is investigated in this paper, and a fault reconstruction method based on adaptive sliding mode observer is proposed. Firstly, the matching condition of the observer is satisfied by constructing an auxiliary output, and a new state variable is selected as the low-pass filter with the fault vector output. Then an adaptive sliding mode observer is designed for the auxiliary output system in the present of the unknown upper bound of the fault, in which the adaptive switching gain is updated online. The gain matrix of the observer is obtained by solving a LMI optimization problem. And a linear transforming matrix is introduced to realize the direct estimation of the fault by the principle of the equivalent control output error injection. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

关键词： continuous casting mold sensor fault reconstruction adaptive sliding mode observer equivalent control output error injection

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Identification of Cancer Development Related Pathways Based on Co-Expression Analyses

Identification of Cancer Development Related Pathways Based ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Hongyang Jiang Zhihang Wang Chaoyi Yin Peishuo Sun Ying Xu Huiyan Sun School of Artificial Intelligence Jilin University Changchun Innovation Group of Marine Engineering Materials and Corrosion Control Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China College of Computer Science and Technology Jilin University Changchun China School of Artificial Intelligence Jilin University Changchun China Computational Systems Biology Lab Institute of Bioinformatics University of Georgia Athens USA School of Artificial Intelligence Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Cancer is a rapidly evolving disease, with complex physiological changes throughout its development. Different patients of the same cancer type may require distinct treatments depending on the level of development. Hence it is essential to identify the genes and biological processes strongly associated with cancer progression to design an effective treatment plan. Our study has found that cancer samples of the same development stage (or grade, subtype) tend to share highly unique co-expression patterns, providing considerably stronger discerning power than differential expressions for cancer staging (and grading, subtyping). Based on this, we have developed a framework for identification and analyses of genes and pathways strongly associated with a cancer's development through identification of co-expression patterns that become increasingly stronger or weaker over cancer samples from early through advanced stages. Functional analyses of such co-expressed genes reveal that (1) cell-cycle, immune response, ribosome, proteasome and oxidative phosphorylation, among others, strongly associate with cancer development, (2) the co-expression patterns among ribosome, proteasome and oxidative phosphorylation genes tend to become increasingly weaker as a cancer advances, for almost all cancer types, and (3) the co-expression patterns among cell cycle and immune response genes tend to become increasingly stronger with cancer progression. We anticipate that co-expression-based analyses like we present here will become a key technique for functional studies of cancer development and evolution.

关键词： Cancer Correlation Indexes Biological processes Physiology Immune system Genetic expression

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Collective dynamics and control for multiple unmanned surface vessels

arXiv

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arXiv 2019年

作者： Liu, Bin Chen, Zhiyong Zhang, Hai-Tao Wang, Xudong Geng, Tao Su, Housheng Zhao, Jin Guangdong HUST Industrial Technology Research Institute Guangdong Province Key Lab of Digital Manufacturing Equipment Dongguan523808 China School of Electrical Engineering and Computing University of Newcastle CallaghanNSW2308 Australia School of Automation State Key Lab of Digital Manufacturing Equipment and Technology Key Lab of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 China School of Automation Key Lab of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 China

A multi-unmanned surface vessel (USV) formation control system is established on a novel platform composed of three 1.2 meter-long hydraulic jet propulsion surface vessels, a differential GPS reference station, and inter-vessel Zigbee communication modules. The system is also equipped with an upper level collective multi-USV protocol and a lower level vessel dynamics controller. The system is capable of chasing and surrounding a target vessel. The results are supported by rigorous theoretical analysis in terms of asymptotical surrounding behavior and trajectory regulation. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed hardware and software architectures. Copyright © 2019, The Authors. All rights reserved.

关键词： Unmanned surface vehicles

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Target tracking based on KCF combining with spatio-temporal context learning

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International Journal of Performability engineering 2018年第2期14卷 386-395页

作者： Wang, Aili Yang, Zhennan Chen, Yushi Iwahori, Yuji Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Harbin150080 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China Dept of Computer Science Chubu University Aichi Japan

Most target tracking is based on a lot of samples training to build the model of the target, which is then carried on the tracking processing. This will need to choose a lot of tracked target samples for learning and training. However, there are all kinds of deformation of the training samples, including variety of light and scale, and so on, causing the long computation time, high computational complexity, and less robustness. The traditional kernel correlation filtering (KCF) tracking is through online learning of the first frame in the target vide. It then uses cyclic matrix to strengthen samples robustness, reducing the complexity of the calculation and time. But, the traditional KCF nuclear is unsatisfactory used for complex scenarios and quick treatment. In this paper, under the framework of the KCF, the target context information is introduced to make the tracking have better robustness and a better effect to deal with complex scenarios. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Target tracking

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