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Onboard Sensing for Drone to Fly Through a Gate with a Rotating Arm

Onboard Sensing for Drone to Fly Through a Gate with a Rotat...

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international conference on Guidance, Navigation and control, ICGNC 2020

作者： Chen, Wenjie Wang, Zihao Luo, Dong Zhu, Bo Peng, Chen University of Electronic Science and Technology of China Chengdu China Sun Yat-Sen University Guangzhou China

ISBN: (纸本)9789811581540

The paper mainly studied the solution for autonomous control of drone to fly through a rotating obstacle using onboard sensing and computing sources. Especially, the indoor environment is considered, where the global positioning system (GPS) signal is not available. For the estimation of the position of the quadrotor, we proposed the solution based a NVIDIA camera T265 for high-precision and small-delay locating. The real-time detection of the rotating obstacle is achieved by a monocular color camera. First, the histogram equalization technique is implemented to enhance the details of the obstacle, then the color feature is used to detect the target, and finally the angular velocity of the rotating obstacle is estimated by each time it appears at a specific location in the image. The PID controllers with proper gains are adopted for the position and attitude control of our drone. The gains of the attitude controller are tuned first, and after the quadrotor can track the desired attitude angle well, the parameters of the position control are tuned. The results of preliminary experiment show that our drone can estimate its own attitude and position indoors through a binocular camera, and that the angular position and angular velocity of the rotating obstacle are well estimated via the proposed detection algorithm. The overall solution, including the cascade PID controllers, is finally verified in Gazebo simulator. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Three term control systems

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AI Based Security for Internet of Transportation Systems

AI Based Security for Internet of Transportation Systems

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Smart Electronics and Communication (ICOSEC), international conference on

作者： Heena Kousar Shaista Fatima Syed Imran Ahmed S. Sajithra Sumit Kushwaha N.Alangudi Balaji Department of Computer Science and Engineering East Point College of Engineering and Technology Bengaluru Karnataka India Department of Electronics and Communication Engineering MJ College Hyderabad Telangana India Department of Computer Science Engineering R.M.K. Engineering College Kavaraipettai Tamilnadu India Department of Computer Applications University Institute of Computing Chandigarh University Punjab India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

The intelligent transportation systems (ITS) use a combination of sensors, cameras, and communication technologies to provide real-time data on traffic conditions. This data can be used to adjust traffic lights, but it can also be used to provide information to drivers, such as real-time traffic updates and recommended routes. Overall, control of traffic lights is an effective solution to address traffic congestion problems in urban areas. By optimizing traffic flow, cities can reduce travel times, improve safety, and reduce emissions from idling vehicles. However, the success of these systems depend on the effective planning, implementation, and ongoing maintenance to ensure that they continue to meet the changing needs of the city. In this work, the interest is to control of traffic lights in order to solve problems related to congestion; in this sense, it is proposed five mechanisms to make traffic lights intelligent and not automatic based on machine learning. The mechanisms implemented are based on four algorithms of machine learning: decision tree (DT), support vector machine (SVM), k nearest neighbor (KNN) and random forest (RF). The solutions obtained make it possible to predict the decision in order to act in traffic depending on several parameters such as the road, cars, passengers etc.

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Genetic Fuzzy Tree Based Learning Algorithm Toward the Weapon-Target Assignment Problem

Genetic Fuzzy Tree Based Learning Algorithm Toward the Weap...

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international conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Li, Jie Wang, Rui Nantogma, Sulemana Xu, Yang University of Electronic Science and Technology of China Chengdu China Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China

ISBN: (纸本)9789811694912

Weapon-target assignment (WTA) is essential ability for command and control (C2) systems. The requirement for real-time decision-making, heterogeneous combat platforms are required to make effective weapon-target assignment decisions to achieve interception of fast and multi-batch targets. Since it is difficult to form an accurate modeling of the incoming target ability and obtain a large amount of training data in actual combat exercises, this problem has become a representative problem of real-time decision-making under the constraints of small training samples. Inspired by the use of rules to make coordinated air defense decisions when manned, we propose a practical rule-based machine learning approach to solve this problem in this paper. Firstly, we model heterogeneous combat platforms into multi-agents system and use genetic fuzzy trees (GFT) to make weapon-target assignment decisions. Genetic algorithm (GA) is then employed to learn fuzzy rules and tune membership functions. To evaluate the performance of the proposed algorithm, we build a typical Surface Unmanned System air defense simulation scenario that employs an auto-fire strategy as baseline. The simulation results show that our approach demonstrates a superior performance over the auto-fire strategy and can greatly improve the interception efficiency with a small amount of training data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Particles Swarm Optimization for Minimal Energy Consumption in Complex Networks Node Search 17

Particles Swarm Optimization for Minimal Energy Consumption ...

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17th international conference on electrical engineering, computing science and automatic control, CCE 2020

作者： Lizarraga, Jorge A. Vega, Carlos J. Sanchez, Edgar N. CINVESTAV-IPN Electrical Engineering Department Guadalajara Mexico University of Naples Federico Ii Department of Electrical Engineering and Information Technology Naples Italy

ISBN: (纸本)9781728189871

In this paper, a new optimization scheme, for minimal energy consumption, is proposed based on a heuristic approach to achieve synchronization in complex networks;the main objective is to determine nodes and gains for the pinning control technique by means of a particles swarm algorithm. A stability equation is used to determine the pinned nodes. The particles swarm seek for a set of nodes and gains, which guarantees asymptotic stability with the minimum number of nodes and simultaneously minimizing energy consumption. The proposed heuristic algorithm is a modification of the particle swarm optimization one. Applicability of the proposed scheme is tested via simulations. © 2020 IEEE.

关键词： Energy utilization

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Identification of Window Openness in Smart Buildings by Random Forest Algorithm 5

Identification of Window Openness in Smart Buildings by Rand...

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5th IEEE international conference on Smart Systems and Technologies, SST 2022

作者： Jelić, Luka Kenda, Jurica Banjac, Anita Rukavina, Filip Lešić, Vinko Laboratory for Renewable Energy Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

controlled energy distribution and energy efficiency in buildings are among the main concerns in modern constructions, energy management and buildings usability. Total energy performance of a building depends on several factors, which include materials and components, building environment, but also the occupants behavior. User interaction with windows and window status as open or closed is the main cause of the difference between the predicted and the actual energy consumption. Understanding these user habits helps to better predict energy disruptions and enables planning for more efficient energy distribution. This paper investigates the possibility of using a machine learning model to identify the user behavior through a set of available historical data in a living-lab smart building. The random forest algorithm used in this research proved promising for the particular use case and makes a good ground for future work with window status classification accuracy of 87.85%. © 2022 IEEE.

关键词： Energy utilization

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Sliding-window informed RRT∗: A method for speeding up the optimization and path smoothing

Sliding-window informed RRT∗: A method for speeding up the ...

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2021 IEEE international conference on Real-Time computing and Robotics, RCAR 2021

作者： Li, Chenming Wang, Chaoqun Wang, Jiankun Shen, Yutian Meng, Max Q.-H. The Chinese University of Hong Kong Department of Electronic Engineering N.T. Shatin Hong Kong School of Control Science and Engineering Shandong University Jinan China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China

ISBN: (纸本)9781665436786

Path planning plays a vital role in robot navigation and manipulation, and multiple types of algorithms have been introduced to address this problem. Rapidly-exploring Random Tree (RRT) based algorithms have many advantages over other path planning algorithms. For example, RRT is suitable to solve the path planning problem in high dimensional space and can easily handle robot differential constraints. Informed RRT∗ is a method that uses the prolate hyper-spheroid to speed up the optimization process, but its efficiency will decrease to the same level as RRT∗ when the hyper-spheroid covers most of the state space. To overcome this drawback, we further propose a Sliding-Window Informed RRT∗ (SWIRRT∗), which combines the sliding-window thought into the Informed RRT∗, taking the advantage of the initial path and make the path optimization much faster. Simulations in 2D space have been carried out to demonstrate that our proposed method can improve the RRT-like algorithm's convergence speed. © 2021 IEEE.

关键词： Motion planning

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Analyzing Security and Privacy issues for Multi-Cloud Service Providers Using Nessus

Analyzing Security and Privacy issues for Multi-Cloud Servic...

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international conference on Electronics, Communication and computing Technologies (ICECCT)

作者： Tarlok Singh Ajay Kumar Department of Computer Science and Engineering Chandigarh University Chandigarh India

Cloud computing security is a broad term that covers a wide range of security and privacy issues for businesses that use multi-cloud services. The service providers must take several factors into account when addressing security for their clients, including access and identity control, in-transit, and other security factors such as confidentiality, vulnerability management, threats, and audits. This paper takes a close look at each of these areas of cloud security and shows how multi-cloud service providers can protect themselves and move forward. It also talks about the problems with protecting systems that use more than one cloud and gives ways to deal with these problems. The reader should understand all of the security concerns that come with multi-cloud setups and how to deal with them in light of the latest cyber threats. The sole motivation of this paper is to raise awareness about multi-cloud service security in different aspects and its impact. Nessus, which is a well-known security tool, has been used to find vulnerabilities and other critical security concerns. Overall, experiments have been performed on three different websites: “***”, “***” and “***”. Despite this, the mitigation approaches for each vulnerability are explained systematically.

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Small-Signal Modelling and Analysis of Converter Interactivity in Low-Voltage DC Grid 6

Small-Signal Modelling and Analysis of Converter Interactivi...

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6th IEEE international conference on computing, Communication and Automation, ICCCA 2021

作者： Sahoo, Himansu Kapat, Santanu Singh, Bhim Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India Indian Institute of Technology Kharagpur Department of Electrical Engineering Kharagpur721302 India

ISBN: (纸本)9781665414739

Due to easy amalgamation with sustainable energy sources, storage units and electric loads, DC grid system is getting more research attention in current times. With the aim of achieving a reliable as well as flexible DC common bus system, it is preferred to operate multiple DC-DC converters in parallel connected architecture. However, due to the parallel connection among converters, coupling effect is observed during the operation. For a smooth controlling of overall system, proper modelling needs to be done. This paper analyses a detailed small signal based model approach for parallel connected DC converters operating with droop control algorithm. An approximation of small ripple in inductor current is considered for modelling. Effect of coupling is taken in to account during modelling process. The presence of cable resistance has direct effect on location of zero in the right-half-plane for derived control to individual converter output voltage transfer function. The controller is designed using the coupled model to achieve suitable stability margin. The correctness of designed model and controller is verified using simulation studies. © 2021 IEEE.

关键词： DC-DC converters

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Enhancing Frequency Regulation of Microgrid using Optimized Two-level Fractionalized TD-PI Strategy

Enhancing Frequency Regulation of Microgrid using Optimized ...

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IEEE international conference on Smart Grid Communications (SmartGridComm)

作者： Abdul Latif Abdelhakim Saim Azeddine Houari Ali Djerioui Institut de Recherche en Énergie Électrique de Nantes Atlantique IREENA Nantes Université Saint-Nazaire France Department of Electrical Engineering Faculty of Technology LGE Laboratoire de Génie Electrique University of M’Sila Msila Algeria

ISBN: (数字)9798350318555

ISBN: (纸本)9798350318562

In today’s microgrid (μG) scenario, participation of various renewable energy sources (RES) in active power control has been increased. Among the various RES, solar and wind power became popular due to their simplicity and eco-friendly nature. But, the active participation of these sources reduces the system inertia. Besides the load changes, RES intermittency and reduced system inertia will cause large frequency excursions in the μG. Optimal PID controllers are failed to provide best performance due to improper tradeoff between integral and derivate controllers. To overcome this problem, in this paper, a modified two-level fractionalized tilt derivative (TD)-PI (TLF(TD)-PI) approach is proposed. The PD-PI and TLF(TD)-PI are employed with diesel generator (DGN), hydrogen fuel cell (HFC) to control their power generation to maintain the desired frequency level under different contingencies. In the suggested method, TD controller is incorporated in primary frequency control, PI controller is incorporated in secondary frequency control. The parameters of the TLF(TD)-PI controller are tuned by using Quadratic Interpolation Technique (QIT) algorithm. The proposed approach with the QIT algorithm was tested against various operating scenarios. Investigation of the responses shows that QIT based TLF(TD)-PI controller gives better response compare to the QIT based ITDF controller.

关键词： Interpolation automatic frequency control Time-frequency analysis Renewable energy sources Power control Microgrids Wind power generation Smart grids Frequency control Tuning

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STAR-RIS Enhanced UAV-MEC Networks: Bi-Directional Task Offloading

STAR-RIS Enhanced UAV-MEC Networks: Bi-Directional Task Offl...

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IEEE international conference on Communications in China (ICCC)

作者： Han Xiao Xiaoyan Hu Weile Zhang Wenjie Wang Kai-Kit Wong Kun Yang School of Information and Communications Engineering Xi’an Jiaotong University Xi’an China Department of Electronic and Electrical Engineering University College London London U.K School of Computer Science and Electronic Engineering University of Essex Colchester U.K

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

This paper introduces a novel multi-user mobile edge computing (MEC) scheme facilitated by simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and unmanned aerial vehicle (UAV). Unlike existing MEC approaches, the proposed scheme enables bi-directional offloading, allowing users to concurrently offload tasks to the MEC servers located at the ground base station (BS) and UAV with STAR-RIS support. Specifically, we formulate an optimization problem aiming at maximizing the amount of the offloaded tasks of users while ensuring the quality of service (QoS) constraints by jointly optimizing the resource allocation, user scheduling, passive beamforming of the STAR-RIS, and the UAV trajectory. A block coordinate descent (BCD) iterative algorithm designed with the successive convex approximation (SCA) technique is proposed to effectively handle the formulated non-convex optimization problem with strongly coupled variables. Simulation results indicate that the proposed STAR-RIS enhanced UAV-enabled MEC scheme possesses significant advantages in enhancing the system’s computational capability over other baseline schemes including the conventional RIS-aided scheme.

关键词： Simulation Quality of service Bidirectional control Reconfigurable intelligent surfaces Autonomous aerial vehicles Trajectory Servers

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