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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Nasr, Salah Abadi, Amine Bouallegue, Kais Mekki, Hassen Laboratory of Networked Objects Control and Communication Systems National Engineering School of Sousse University of Sousse Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse Tunisia

ISBN: (纸本)9789897583216

This paper deals with the complex chaotic behavior that can appear in the dynamic trajectory of a mobile robot, when the robot is broken or partly damaged. However, a flatness-based controller is designed to ensure the trajectory planning and tracking. Different mathematical tools have been used such as the flatness control technique and non linear chaotic systems. The simulation results for the kinematic controller are presented to demonstrate the effectiveness of this approach. Copyright © 2018 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved

关键词： Mobile robots

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Event-triggered control for a class of second-order uncertain p-normal nonlinear systems

Event-triggered control for a class of second-order uncertai...

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第三十八届中国控制会议

作者： Wei Jiang Ting Li Zhenhua Zhao Department of Electronic Information Wuxi Vocational Institute of Arts & Technology the School of Automation Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education College of Automation Engineering Nanjing University of Aeronautics and Astronautics

The problem of event-triggered control for a class of second-order uncertain nonlinear systems subject to p-norm is investigated in this paper. A novel in this paper is that the input-to-state stability(ISS) assumption is removed. By adding a power integrator technique, we design a virtual control signal to address the uncertainties and nonlinearities of nonlinear *** rigorous stability analysis, all the signals of the closed-loop system are proven to be globally uniformly bounded and can converge to an arbitrarily small set which can be be adjusted by one parameter. A numerical example demonstrates the effectiveness of the designed scheme.

关键词： Event-triggered control uncertain nonlinear systems p-norm adding a power integrator technique

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Humidity error compensating of MEMS gyros based on a daptive threshold denoising and RBF neural network 37

Humidity error compensating of MEMS gyros based on a daptive...

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37th Chinese control Conference, CCC 2018

作者： Xin-Wang, Wang Xiao-Lin, Shen Hui-Liang, Cao Bo-Wen, Deng North University of China School of Electrical and Control Engineering Taiyuan030051 China North University of China Science and Technology on Electronic Test Measurement Laboratory Taiyuan030051 China North University of China School of Information and Communication Engineering Taiyuan030051 China

ISBN: (纸本)9789881563941

The large random errors in a typical MEMS gyros under the ranges of relative humidity condition. In order to solve the large random error under the ranges of relative humidity, a method based on adaptive threshold denoising and neural network is proposed in this paper. Full relative humidity experiment is carried to test LSM6DS3 MEMS gyros. Then the adaptive threshold denoising is used to separate the drift error and drift data modeled with RBF neural network. The experimental results show the effectiveness of the method, and it is of great significance in improving the performance of MEMS gyros. © 2018 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Random errors

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Piezoelectric thermoelastic dissipation research of piezoelectric harvester under different vibration 2

Piezoelectric thermoelastic dissipation research of piezoele...

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2nd International Conference on Electronic Information technology and Computer engineering, EITCE 2018

作者： Liu, Yuting Deng, Jiahao Ye, Yong Hou, Zhuo Duan, Zuodong Xu, Sha School of Mechatronical Engineering Beijing Institute of Technology Beijing100081 China Science and Technology on Electromechanical Dynamic Control Laboratory Beijing Institute of Technology Beijing100081 China College of Information Engineering Shenzhen University Shenzhen518060 China National Key Laboratory of Electronic Measurement Technology North University of China Taiyuan030051 China

Piezoelectric materials are widely used to form piezoelectric energy harvesters. Also, the thermoelastic dissipation always influences the energy harvesting efficiency, during the energy harvest process. Therefore, in this paper, we discuss the effect of thermoelastic dissipation on the piezoelectric harvester through numerical calculation, simulation and experiment. The piezoelectric thermoelastic coupling governing equations under different vibration are derived, which are based on the Euler-Bernoulli beam theory, thermal conduction model and piezoelectric field model. Then, the structure frequency shift and thermoelastic damping are studied via numerical calculation and simulation. Meanwhile, we show the influence of the temperature field on the piezoelectric structure under different vibration modes. Furth more, we research the variations of piezoelectric structure thermoelastic dissipation characteristics under different structure geometry sizes. Based on these analyses, the effect of piezoelectric thermoelastic dissipation on the piezoelectric harvester is researched © The Authors, published by EDP Sciences, 2018.

关键词： Energy harvesting

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Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges

arXiv

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arXiv 2019年

作者： Feng, Di Haase-Schutz, Christian Rosenbaum, Lars Hertlein, Heinz Glaser, Claudius Timm, Fabian Wiesbeck, Werner Dietmayer, Klaus Driver Assistance Systems and Automated Driving Corporate Research Robert Bosch GmbH Renningen71272 Germany Institute of Measurement Control and Microtechnology Ulm University Ulm89081 Germany Engineering Cognitive Systems Automated Driving Chassis Systems Control Robert Bosch GmbH Abstatt74232 Germany Institute of Radio Frequency Engineering and Electronics Karlsruhe Institute of Technology Karlsruhe76131 Germany

Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple sensing modalities can be fused to exploit their complementary properties. In this context, many methods have been proposed for deep multi-modal perception problems. However, there is no general guideline for network architecture design, and questions of "what to fuse", "when to fuse", and "how to fuse" remain open. This review paper attempts to systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving. To this end, we first provide an overview of on-board sensors on test vehicles, open datasets, and background information for object detection and semantic segmentation in autonomous driving research. We then summarize the fusion methodologies and discuss challenges and open questions. In the appendix, we provide tables that summarize topics and methods. We also provide an interactive online platform to navigate each reference: Https://***/multimodalperception/. Copyright © 2019, The Authors. All rights reserved.

关键词： Object detection

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Coordinated control method of virtually coupled train formation based on multi agent system 2nd

Coordinated control method of virtually coupled train format...

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2nd International Conference on Smart Vehicular technology, Transportation, communication and Applications, VTCA 2018

作者： Liu, Ling Wang, Ping Zhang, Bo Wei, Wei School of Software and Microelectronics Peking University Beijing102600 China Beijing National Railway Research and Design Institute of Signal and Communication Group Co. Ltd. Beijing100070 China Beijing Engineering Technology Research Center of Operation Control Systems for High Speed Railways Beijing100070 China National Engineering Research Center for Software Engineering Peking University Beijing102600 China Key Laboratory of High Confidence Software Technologies Peking University Beijing102600 China

ISBN: (纸本)9783030045814

As China has become the country with the longest operating mileage and largest construction scale of high-speed railway (HSR) in the world, how to improve the operational excellence and customer satisfaction draws increasing attention. In order to further optimize the allocation of transport resource and improve the transportation efficiency of HSR, a coordinated control method using the idea of virtual coupling (VC) based on multi agent system (MAS) is proposed in this paper firstly. At last, the efficiency and feasibility of proposed model and method are demonstrated using a simulation case, which shows that the coordinated control model based on MAS can not only ensure the safety of operation, but also improve the efficiency of a whole train group. © Springer Nature Switzerland AG 2019.

关键词： Multi agent systems

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Secure communications in a unified non-orthogonal multiple access framework

arXiv

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arXiv 2019年

作者： Yue, Xinwei Liu, Yuanwei Yao, Yuanyuan Li, Xuehua Liu, Rongke Nallanathan, Arumugam School of Information and Communication Engineering Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom School of Electronic and Information Engineering Beihang University Beijing100191 China

This paper investigates the impact of physical layer secrecy on the performance of a unified non-orthogonal multiple access (NOMA) framework, where both external and internal eavesdropping scenarios are examined. The spatial locations of legitimate users (LUs) and eavesdroppers are modeled by invoking stochastic geometry. To characterize the security performance, new exact and asymptotic expressions of secrecy outage probability (SOP) are derived for both code-domain NOMA (CD-NOMA) and power-domain NOMA (PD-NOMA), in which imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) are taken into account. For the external eavesdropping scenario, the secrecy diversity orders by a pair of LUs (the n-th user and m-th user) for CD/PD-NOMA are obtained. Analytical results make known that the diversity orders of the n-th user with ipSIC/pSIC for CD-NOMA and PD-NOMA are equal to zero/ K and zero/one, respectively. The diversity orders of the m-th user are equal to K/one for CD/PD-NOMA. For the internal eavesdropping scenario, we examine the analysis of secrecy diversity order and observe that the m-th user to wiretap the n-th user with ipSIC/pSIC for CD-NOMA and PDNOMA provide the diversity orders of zero/K and zero/one, respectively, which is consistent with external eavesdropping scenario. Numerical results are present to confirm the accuracy of the analytical results developed and show that: i) The secrecy outage behavior of the n-th user is superior to that of the m-th user;ii) By increasing the number of subcarriers, CD-NOMA is capable of achieving a larger secrecy diversity gain compared to PD-NOMA. Copyright © 2019, The Authors. All rights reserved.

关键词： Geometry

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An Algorithm of Object Detection Based on Regression Learning for Remote Sensing Images

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Journal of Physics: Conference Series 2021年第1期1903卷

作者： Jiajia Wang Ran Wu Xiaqiong Yu Beijing Jinghang Research Institute of Computing and Communication Beijing 100076 China Applied Mathematics Research Center of CASIC Beijing 100076 China Beijing Air Traffic Control Engineering Technology Co. Ltd Beijing 100621 China 32021 Troops Beijing 100094 China

Saliency detection method is widely used in the field of object detection. It can greatly improve the efficiency of detection by extracting the region that may contain the objects and reduce the processing of background area. It is very difficult to detect the airports in remote sensing image for its changeable structure and complex background. Considering this situation, this paper proposes a object detection method of saliency model based on regression learning, this method extracts salient regions that may contain airports, and then detects salient regions through feature bag model. Our method uses super-pixel segmentation, minimization of absolute shrinkage and selection operator and hierarchical learning theory based on back-propagation. The salient regions that contain potential objects are extracted and sent to the feature bag model for classification. and it can location the final objects. This paper constructs the airport training dataset and test dataset, and the experimental results fully prove the effectiveness and superiority of this method.

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Evolution and contributions of internet of medical things aided emergency COVID-19 health monitoring and quarantine management

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AIP Conference Proceedings 2023年第1期2603卷

作者： Shahanawaj Ahamad Melanie Elizabeth Lourens Shvets Yuriy Yurievich Chandra Kumar Dixit Ruchi Kalra Swaminathan Ramamurthy Department of Information and Computer Sciences College of Computer Science and Engineering University of Hail Hail City Saudi Arabia Department of Human Resources Management Durban University of Technology South Africa Department of Economical Development Institute of Control of Science Trapeznikov. RAS Financial University under the Government of Russion Federation Russia Department of Physics Dr. Shakuntala Misra National Rehabilitation University Lucknow 226017 Uttar Pradesh India IIS (Deemed to Be University) Jaipur 302 020 Rajasthan India Department of Home Science Guru Nanak College Sri Muktsar Sahib 152026 Punjab India Department of Electronics and Communication Engineering Saveetha school of Engineering Chennai 602105 Tamilnadu India

The present global situation of COVID-19 pandemic has broke through regional, revolutionary, philosophical, spiritual, social, and educational barriers. By utilizing an interconnection of network, an Internet of Things enabled medical system is useful for regular monitoring of COVID-19 patients. It also aids in improving patient experience and reducing re-hospitalizations. The arrival of the IoT has effect on reducing healthcare costs and enhancing the treatment outcome of affected patients. As a result, the goal of this study is to analyze and emphasize the overall applicability of the well-established IoT concept by providing a conceptual outlay to combat the COVID-19 pandemic.

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Preprocessing method of night vision image application in apple harvesting robot

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International Journal of Agricultural and Biological engineering 2018年第2期11卷 158-163页

作者： Weikuan Jia Yuanjie Zheng De’an Zhao Xiang Yin Xiaoyang Liu Ruicheng Du School of Information Science and Engineering Shandong Normal UniversityJinan 250358China Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Jiangsu UniversityZhenjiang 212013China School of Agricultural Engineering and Food Science Shandong University of TechnologyZibo 255000China Institute of Life Sciences and Key Lab of Intelligent Information Processing Shandong Normal UniversityJinan 250014China

Due to the low working efficiency of apple harvesting robots,there is still a long way to go for *** machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots,this study focused on the extended operating time and proposed a round-the-clock operation *** to the influences of light,temperature,humidity,etc.,the working environment at night is relatively complex,and thus restricts the operating efficiency of the apple harvesting *** different artificial light sources(incandescent lamp,fluorescent lamp,and LED lights)were selected for auxiliary light according to certain rules so that the apple night vision images could be *** addition,by color analysis,night and natural light images were compared to find out the color characteristics of the night vision images,and intuitive visual and difference image methods were used to analyze the noise *** results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night,and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper *** preprocessing method can provide a theoretical and technical reference for subsequent image processing.

关键词： apple harvesting robot night vision image preprocessing method color analysis noise analysis

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