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Design of robust controller applied for series elastic actuators in controlling Humanoid's joint

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arXiv 2021年

作者： Luu, Anh Khoa Lanh Duong, Van Tu Nguyen, Huy Hung Kim, Sang Bong Nguyen, Tan Tien National Key Laboratory of Digital Control and System Engineering Ho Chi Minh City University of Technology VNU-HCM Hochiminh city Viet Nam Department of Mechatronics Ho Chi Minh City University of Technology VNU-HCM Hochiminh city Viet Nam Faculty of Electronics and Telecommunication Saigon University Viet Nam Pukyong National University Busan Korea Republic of

Although the application of Series elastic actuators (SEAs) in the biomechatronic field has proved its appropriation in many aspects so far, the problems of maintaining the stability for the SEAs still remains. This paper proposes a robust controller so that to overcome the drawbacks of the previous researches. Firstly, a mathematical model considering both the SEAs and the hip joint of humanoid UXA-90 is obtained. Secondly, a reference input of the proposed controller that is achieved from desired hip joint's angle in a walking cycle is utilized. Then, a backstepping based sliding mode force control approach is employed to ensure the precise movement of robot's link as well as meeting the requirement of robustness for the whole system, which is significant for the task of walking of a humanoid. Finally, some simulations are carried out to verify the quality and effectiveness of the proposed controller. © 2021, CC BY.

关键词： Sliding mode control

CBAM-GAN: Generative Adversarial Networks Based on Convolutional Block Attention Module 5th

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CBAM-GAN: Generative Adversarial Networks Based on Convoluti...

5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Ma, Bing Wang, Xiaoru Zhang, Heng Li, Fu Dan, Jiawang Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering Portland States University Portland United States

ISBN: (纸本)9783030242732

Generating images using generative adversarial networks (GAN) is one of the research hotspots. The traditional convolutional GAN treats spatial and channel-wise features equally, which causes the lack of flexibility in extracting features from the discriminator and the generator. To address the issue, we propose generative adversarial networks based on convolutional block attention module (CBAM-GAN) in this paper. CBAM-GAN adds the convolutional block attention module after some convolution operators to adaptively rescale spatial and channel-wise features, which can enhance salient regions and extract more detail features. We apply the network framework of CBAM-GAN to popular GAN models and do an empirical study on MNIST and CIFAR-10 datasets. Experiments show that our model can significantly improve the quality of generated images compared with the traditional convolutional GAN. © 2019, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

UAV-assisted and intelligent reflecting surfaces-supported terahertz communications

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arXiv 2020年

作者： Pan, Yijin Wang, Kezhi Pan, Cunhua Zhu, Huiling Wang, Jiangzhou The National Mobile Communications Research Laboratory Southeast University Nanjing211111 China The School of Engineering and Digital Arts University of Kent United Kingdom The Department of Computer and Information Sciences Northumbria University United Kingdom The School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom

In this paper, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications. To this end, the joint optimization of UAV's trajectory, the phase shift of IRS, the allocation of THz sub-bands, and the power control is investigated to maximize the minimum average achievable rate of all the users. An iteration algorithm based on successive Convex Approximation with the Rate constraint penalty (CAR) is developed to obtain UAV's trajectory, and the IRS phase shift is formulated as a closed-form expression with introduced pricing factors. Simulation results show that the proposed scheme significantly enhances the rate performance of the whole system. © 2020, CC BY.

关键词： Unmanned aerial vehicles (UAV)

Auto landing system on a fixed wing unmanned aerial vehicle using linear quadratic approach 5

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Auto landing system on a fixed wing unmanned aerial vehicle ...

5th International Conference on Science and Technology, ICST 2019

作者： Dharmawan, Andi Ashari, Ahmad Handayani, Ariesta Martiningtyas Meirani Utami, Riarsari Tresnayana, I Made Universitas Gadjah Mada Electronics and Instrumentation Research Laboratory Yogyakarta Indonesia Universitas Gadjah Mada Computer System and Networking Research Laboratory Yogyakarta Indonesia Universitas Gadjah Mada Department of Electrical and Informatics Engineering Yogyakarta Indonesia

ISBN: (纸本)9781728123691

The primary control issue on Unmanned Aerial Vehicle (UAV) is to control the rotation motion in the form of pitch, roll, and yaw. These rotational movements are used for various flight phases. The flight phases are at least divided into 3, consisting of taking off, cruising, and landing phases. The landing phase is one of the most critical phases. If the flight control of a UAV in this phase is not optimal, then it can crash. The landing phase control system in this research uses the Linear Quadratic Regulator (LQR) method. This method works on a full-state feedback control system. This control system will produce style and torque, both of which will be converted to PWM (Pulse Width Modulation) signals and the servos deflection angle values. The PWM signals play a role in regulating how fast the brushless motor rotates. The control system is used to maintain the stability of the UAV upon landing so that the UAV does not experience undesirable things. Landing phase testing results show that the control system has been able to land the UAV with an optimal control response. © 2019 IEEE.

关键词： State feedback

Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects

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arXiv 2021年

作者： Ahmad, Muhammad Shabbir, Sidrah Roy, Swalpa Kumar Hong, Danfeng Wu, Xin Yao, Jing Khan, Adil Mehmood Mazzara, Manuel Distefano, Salvatore Chanussot, Jocelyn Department of Computer Science National University of Computer and Emerging Sciences Islamabad Chiniot-Faisalabad Campus Chiniot35400 Pakistan Dipartimento di Matematica e Informatica-MIFT University of Messina Messina98121 Italy Pakistan The Department of Computer Science and Engineering Jalpaiguri Government Engineering College West Bengal 735102 India The Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China The Institute of Data Science and Artificial Intelligence Innopolis University Innopolis 420500 Russia Institute of Software Development and Engineering Innopolis University Innopolis420500 Russia The Univ. Grenoble Alpes CNRS Grenoble INP GIPSA-Lab Grenoble38000 France

Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably, the complex characteristics i.e., the nonlinear relation among the captured spectral information and the corresponding object of HSI data make accurate classification challenging for traditional methods. In the last few years, Deep Learning (DL) has been substantiated as a powerful feature extractor that effectively addresses the nonlinear problems that appeared in a number of computer vision tasks. This prompts the deployment of DL for HSI classification (HSIC) which revealed good performance. This survey enlists a systematic overview of DL for HSIC and compared state-of-the-art strategies of the said topic. Primarily, we will encapsulate the main challenges of traditional machine learning for HSIC and then we will acquaint the superiority of DL to address these problems. This survey breakdown the state-of-the-art DL frameworks into spectral-features, spatial-features, and together spatial-spectral features to systematically analyze the achievements (future research directions as well) of these frameworks for HSIC. Moreover, we will consider the fact that DL requires a large number of labeled training examples whereas acquiring such a number for HSIC is challenging in terms of time and cost. Therefore, this survey discusses some strategies to improve the generalization performance of DL strategies which can provide some future guidelines. © 2021, CC BY.

关键词： Surveys

Attitude and horizontal speed control system on unmanned aerial vehicle using LQR 5

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Attitude and horizontal speed control system on unmanned aer...

5th International Conference on Science and Technology, ICST 2019

作者： Dharmawan, Andi Ichsan, Lazuardi Baskoro, Hanif Istiyanto, Jazi Eko Martiningtyas Handayani, Ariesta Universitas Gadjah Mada Electronics and Instrumentation Research Laboratory Yogyakarta Indonesia Universitas Gadjah Mada Computer System and Networking Research Laboratory Yogyakarta Indonesia Universitas Gadjah Mada Department of Electrical and Informatics Engineering Yogyakarta Indonesia

ISBN: (纸本)9781728123691

Unmanned Aerial Vehicles (UAV) or drones are expected to fly automatically, especially in performing basic maneuvers. The necessary maneuver is to fly straight and level, where no rotation occurs on the roll, pitch, and yaw axes that work on the plane. Also, to free from rotational motion, the aircraft needs to maintain its horizontal speed to prevent the vehicle from losing lift and free-fall. This research uses a Linear Quadratic Regulator (LQR) control method to obtain full-state feedback K gain from the control system. The gain of the full-state feedback is used to control the output, which is converted into Pulse Width Modulation to control the rotational speed of the brushless motor, and the angle of servo. The result of this research is that system response obtained is optimum with the desired specification. © 2019 IEEE.

关键词： Drones

Data protection and provenance in cloud of things environment: Research challenges

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International Journal of Information and computer Security 2020年第4期12卷 416-435页

作者： Wang, Chundong Yang, Lei Guo, Hao Wan, Fujin Key Laboratory of Computer Vision and System Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Ministry of Education Tianjin University of Technology Tianjin China Global Energy Internet Research Institute Beijing University of Technology Tianjin China Department of College of Computer and Control Engineering Nankai University Tianjin China

Internet of things are increasingly being deployed over the cloud (also referred to as cloud of things) to provide a broader range of services. However, there are serious challenges of CoT in the data protection and security provenance. This paper proposes a data privacy protection and provenance model (DPSPM) based on CoT. It can protect the privacy data of the users and trace the source of leaked data. In detail, security encryption and watermarking algorithms are proposed. Meanwhile, we use the improved k-anonymity data masking algorithm and pseudo-row watermarking algorithm in this scheme. Those algorithms can carry out security control over the whole process of data publishing, especially in data encryption, data masking and provenance verification. Finally, the experimental results show that our scheme has good efficiency. It is proved that the data masking time is proportional to the parameters k and L, the results also show good robustness to the common database watermarking attacks. © 2020 Inderscience Enterprises Ltd.

关键词： Data privacy

Low-rank matrix completion: A contemporary survey

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arXiv 2019年

作者： Nguyen, Luong Trung Kim, Junhan Shim, Byonghyo Information System Laboratory Department of Electrical and Computer Engineering Seoul National University

As a paradigm to recover unknown entries of a matrix from partial observations, low-rank matrix completion (LRMC) has generated a great deal of interest. Over the years, there have been lots of works on this topic but it might not be easy to grasp the essential knowledge from these studies. This is mainly because many of these works are highly theoretical or a proposal of new LRMC technique. In this paper, we give a contemporary survey on LRMC. In order to provide better view, insight, and understanding of potentials and limitations of LRMC, we present early scattered results in a structured and accessible way. Specifically, we classify the state-of-the-art LRMC techniques into two main categories and then explain each category in detail. We next discuss issues to be considered when one considers using LRMC techniques. These include intrinsic properties required for the matrix recovery and how to exploit a special structure in LRMC design. We also discuss the convolutional neural network (CNN) based LRMC algorithms exploiting the graph structure of a low-rank matrix. Further, we present the recovery performance and the computational complexity of the state-of-the-art LRMC techniques. Our hope is that this survey article will serve as a useful guide for practitioners and non-experts to catch the GIST of LRMC. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

衰亡链揭示互利共生生态系统中安全与崩溃的中间阶段（英文）

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engineering 2024年第12期 89-98页

作者：王光炜刘雪明肖颖袁烨潘林强管晓宏高建喜张海涛 The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and Technology Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi'an Jiaotong University Tsinghua National Laboratory of Information Science and Technology Department of Automation Tsinghua University Department of Computer Science Rensselaer Polytechnic Institute

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities, such as overfishing and deforestation, and the effects of such damage on ecological stability are uncertain. Despite recent advances in experimental and theoretical studies on regime shifts and tipping points, theoretical tools for understanding the extinction chain, which is the sequence of species extinctions resulting from overexploitation, are still lacking, especially for large-scale nonlinear networked systems. In this study, we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and densities. We discovered five phases during the exploitation process: safe,partial extinction, bistable, tristable, and collapse, which enabled the optimal design of restoration strategies for degraded or collapsed systems. We validated our approach using a 20-year dataset from an eelgrass restoration project. Counterintuitively, we also found a specific region in the diagram spanning exploitation rates and competition intensities, where exploiting more species helps increase *** computational tool provides insights into harvesting, fishing, exploitation, or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

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