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Unveiling the Superiority: Comparative Analysis of ANFIS, FOPID, and PI controllers in Grid-Connected EV Systems for G2V/V2G applications

Unveiling the Superiority: Comparative Analysis of ANFIS, FO...

引用

2023 ieee International conference on Electrical, Electronics, Communication and Computers, ELEXCOM 2023

作者： Yadav, Gaurav Singh, Mukhtiar Delhi Technological University Electrical Engineering Department Delhi India

ISBN: (纸本)9798350305111

For successful Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) operations, it is essential to have a Bi-Directional power exchange between plug-in electric vehicles (PEVs) and the AC electrical grid. This manuscript introduces an Adaptive control-based non-isolated Bi-Directional Buck-Boost converter that effectively manages the charging and discharging of Electric Vehicle (EV) batteries based on reference values. Additionally, the study includes a comparative analysis, evaluating the converter's performance against conventional controllers such as FOPID and PI. Using MATLAB/Simulink, a single-phase On-Board Electric Vehicle Charger is simulated with three different controllers: PI, FOPID, and ANFIS. The comparative analysis clearly demonstrates the superior effectiveness of ANFIS-based controllers over FOPID and PI controllers. © 2023 ieee.

关键词： Fuzzy inference

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Optical Flash switching via Electrically controlled Metasurfaces 18

Optical Flash switching via Electrically Controlled Metasurf...

引用

18th ieee Nanotechnology Materials and Devices conference, NMDC 2023

作者： Kamali, Khosro Zangeneh Xu, Lei Gagrani, Nikita Tan, Hark Hoe Jagadish, Chennupati Miroshnichenko, Andrey Neshev, Dragomir Rahmani, Mohsen Research School of Physics CanberraACT2601 Australia Nottingham Trent University Advanced Optics and Photonics Laboratory Department of Engineering School of Science and Technology NottinghamNG11 8NS United Kingdom University of New South Wales School of Engineering and Information Technology CanberraACT2600 Australia

ISBN: (纸本)9798350335460

Recent advancements in nanofabrications, characterisations and computer modellings allow generating of novel metasurfaces that control the light characteristics in extraordinary ways. Such advances have led to revolutionary applications in several fields, including but not limited to metalenses, polarisation converters, nano-sensors, and holograms [1]. Meanwhile, the active and reversible tunning of metasurfaces has attracted significant attention due to the larger degree of freedom that tunable metasurfaces can offer. Tunning metasurfaces can be obtained by various external stimuli, such as mechanical, electrical, optical, etc. [1]. © 2023 ieee.

关键词： Degrees of freedom (mechanics)

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An Efficient ODR for Computer Night Vision Using Multi-Scale Retinex Network-Aided Enhanced Images 4

An Efficient ODR for Computer Night Vision Using Multi-Scale...

引用

4th International conference on Power, Energy, control and Transmission Systems, ICPECTS 2024

作者： Charles Prabu, V. Pandiaraja, P. Sathiyamoorthi, V. Durgadevi, P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Government Polytechnic College Department of Computer Engineering Baisuhalli Tamilnadu Dharmapuri India Srm Institute of Science and Technology Department of Computer Science and Engineering Vadapalani Campus Tamilnadu Chennai India

ISBN: (纸本)9798331508845

In the current scenario, recognizing various objects and tracking their movements in the real-time surveillance footage is the most difficult task. To detect objects, a combination of image processing and computer vision algorithms is utilized. Computer-vision based automatic human activity recognition from surveillance video can be utilized for applications such as the identification of violent acts and the study of human behavior. Consequently, this work implements a new "Object Detection and Recognition (ODR)"model for computer night vision utilizing a deep learning technique. In order to improve the supplied input image, the combined images are first transmitted to the "Multi-scale Retinex (MSR)"model. The You Only Look Once Version 7 (YoloV7) model uses the improved image from MSR as input to identify and recognize things. After conducting experiments, the implemented ODR model on the ExDark Dataset obtained an efficiency of 94.8%. © 2024 ieee.

关键词： Deep learning

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Utilizing Portable Thermoelectric Generators for Field Power in Military Emergencies 1

Utilizing Portable Thermoelectric Generators for Field Power...

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1st International conference on Smart Mechatronics, ICSMech 2024

作者： Pratama, Muhammad Angga Yoga Orlando, Meky T Rahmatulloh, Muhamad Dahlan, Iqbal Ahmad Republic of Indonesia Defense University Faculty of Defense Science and Technology Bogor Indonesia

ISBN: (纸本)9798350368918

Reliable power access in military field operations, especially in remote or harsh environments, is crucial for mission success. This study explores the potential of portable thermoelectric generators (TEGs) to provide emergency power by converting waste heat into electricity using the Seebeck effect. A portable TEG system was developed, utilizing a stainless steel fireplace as the heat source and ethanol cooling to maintain a significant temperature difference. The system achieved a peak voltage of 7.2V and a stable output of 5V, sufficient to charge a 10,000mAh battery, with a conversion efficiency of approximately 72%. The TEG system reached its maximum output within 20 minutes and maintained steady performance with minimal fluctuations. Its compact and lightweight design allows easy transport and deployment, enabling soldiers to generate power while cooking, thereby supporting critical devices like communication tools and lighting. This innovation enhances operational capabilities and safety while reducing dependence on conventional power sources. Beyond military applications, the technology has potential use in disaster relief and off-grid energy systems, where sustainable, portable power is essential. Future research will focus on improving material efficiency and power output to broaden TEG usability across various scenarios. © 2024 ieee.

关键词： Conversion efficiency

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Economical UWB/IμVO Fusion for Mobile Robot Localization and Mapping in Poultry House

Economical UWB/IμVO Fusion for Mobile Robot Localization an...

引用

2023 International Automatic control conference, CACS 2023

作者： Ke, Jing Y. Jhan, Meng X. Chang, Chung L. National Pingtung University of Science and Technology Department of Biomechatronics Engineering Neipu Taiwan

ISBN: (纸本)9798350306354

This paper presents an economical fusion of ultra-wideband (UWB), inertial measurement unit (IMU), and visual odometer (VO) technologies for indoor mobile robot localization and mapping. Simultaneous localization and mapping (SLAM) technology is employed to construct maps and collaborate with the A∗ search algorithm for path planning. The positioning information obtained from UWB is utilized to enhance dead reckoning and minimize positioning errors. The fusion of precise distance measurements, orientation data, path information, and real-time appearance-based mapping (RTAB-Map) contributes to enhanced positioning accuracy and robustness. Experimental results showcase improved robot localization accuracy and detailed environment mapping. This collaborative approach serves as an affordable solution for various applications, including the autonomous navigation of mobile robots within poultry houses. © 2023 ieee.

关键词： Motion planning

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Light-Weight Congestion control in Constrained IoT Networks

Light-Weight Congestion Control in Constrained IoT Networks

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ieee Global Communications conference (GLOBECOM)

作者： Khalek, Hussam Abdul Mhamdi, Lotfi Univ Leeds Sch Elect & Elect Engn Leeds W Yorkshire England

ISBN: (纸本)9781665435406

The Internet of Things (IoT) is a growing technology that remotely connects multiple devices (ranging across many fields and applications) over the Internet. The scalability of an IoT network mandates a reliable transport infrastructure. Traditional TCP control protocol is unsuitable for such domain, mainly due to energy and power consumption reasons. A lighter version of TCP, Light Weight IP (lwIP) provides a promising solution for current and projected future scalable IoT infrastructures. However, the original lwIP is just a simple mapping of the protocol, without insight into the IoT specific requirements. This paper examines the lwIP congestion control mechanism and addresses its shortcomings. In particular, a detailed examination is devoted to the various metrics such as Retransmission Time-Outs (RTOs) and its back-off epochs, the congestion window behaviour and progress in the absence (and presence) of congestion. In particular, we propose a set of novel algorithms to address both the IoT constraints nature (light-weight) as well as keeping up with scalability in IoT network size and performance. A detailed simulation study has been conducted to endorse the viability of our proposed set of algorithms for next-generation IoT networks.

关键词： Congestion control IoT lwIP TCP

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Intrusion Detection Mechanism Using Deep Learning 5

Intrusion Detection Mechanism Using Deep Learning

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5th International conference on IoT Based control Networks and Intelligent Systems, ICICNIS 2024

作者： Ananthi, P. Nirmaladevi, K. Naveen Kumar, S. Kongu Engineering College Department of Computer Technology-PG Tamilnadu Erode638060 India Madanapalle Institute of Technology & Science Department of Computer Applications India M.Sc Software Systems Kongu Engineering College Erode India

ISBN: (纸本)9798331518097

In today's connected and data-driven world, networks and digital systems need to be protected from malicious attacks. The effectiveness of conventional Intrusion Detection Systems (IDS) in recognizing and impeding novel threats and intricate methodologies has its limits. This study introduces a new method for improving network security by using deep learning techniques in the design and development of an intrusion detection system (IDS). The suggested Intrusion Detection System uses deep learning techniques, specifically Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNNs), to identify and react to known and new security threats. Data can be taught to be encoded into a lower-dimensional representation and then decoded back into its original form using autoencoders (AEs). Autoencoders are a cutting-edge intrusion detection system that can lower false positives and raise overall detection accuracy because of their capacity to automatically learn from and adjust to the ever-changing threat landscape. They enhance computer networks capacity to spot irregularities and possible security threats. With the deep learning model obtaining a high accuracy of 99% in real-world threat detection, the results show that deep learning is effective in developing intrusion detection systems. © 2024 ieee.

关键词： Network intrusion

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Assessment of Quadrotor PID control Algorithms using six-Degrees of Freedom CFD simulations 61

Assessment of Quadrotor PID Control Algorithms using six-Deg...

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ieee 61st conference on Decision and control (CDC)

作者： Ruiz, Manuel Carreno Bloise, Nicoletta Capello, Elisa D'Ambrosio, Domenic Guglieri, Giorgio Politecn Torino Dept Mech & Aerosp Engn Corso Duca Abruzzi 24 I-10129 Turin Italy Politecn Torino CNR IEIIT Corso Duca Abruzzi 24 I-10129 Turin Italy

ISBN: (纸本)9781665467612

The evolution of technology has made increasingly advantageous the introduction of Unmanned Aerial Systems (UASs) in various applications, especially by exploiting their ability for autonomous flight. This paper presents an innovative approach to simulating UAS maneuvers that integrates a Computational Fluid Dynamics (CFD) model and a closed-loop control algorithm for both position and attitude dynamics. We chose the Proportional-Integrative-Derivative (PID) controller for this preliminary research activity because of its simple implementation and widespread employment in commercial autopilot systems. The numerical simulation of the UAS aerodynamics allows for performing an accurate analysis in critical situations. These include, for example, ground effect or wind gusts scenarios, which require an enhanced propulsive model to capture the interaction between vehicle dynamics, aerodynamics, and environmental conditions. The coupled CFD/PID framework can be a virtual testing environment for UAS platforms. Here we report on its validation. The paper compares such an innovative in-the-loop CFD approach and a classical simplified propulsive model that adopts constant thrust and torque coefficients.

关键词： Unmanned Aerial Systems PID controller Computational Fluid Dynamics

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DSR Based Routing for Smart Gird with 64-Bit Key Management

DSR Based Routing for Smart Gird with 64-Bit Key Management

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2024 International conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence, RAEEUCCI 2024

作者： Ramya, R.R. Banumathi, J. University College of Engineering Department of Information Technology Tamilnadu Nagercoil India

ISBN: (数字)9798350354539

ISBN: (纸本)9798350354539

The world is moving towards smart grid technology because of the complications in traditional grid system and enormous demand for electricity. The traditional grid systems have unidirectional power flow, but smart grid has bi-directional power flow between providers and customers. When IoT technology and Smart Grids (SG) are combined together, it allows for accurate power consumption assessment and monitoring. Hence, an Internet of Things (IoT) based smart grid system is introduced in this paper. In this method, frequency and speed of Wind Energy Conservation System (WECS) as well as current and voltage of Photovoltaic (PV) systems are monitored through IoT module, which are then viewed in IoT webpage. The suggested method enables to monitor and control the generation of electricity precisely. However, packet data loss leads to data leakage which results in the lack of security in data transfer. Hence, a 64 bit cryptographic key management technique is employed for secure and enhanced data transfer and Dynamic Source Routing (DSR) protocol is utilized to determine the shortest path for data transferring. By enabling secure encryption method and congested-free data transfer with routing protocol, IoT based SG applications boosts the system's overall efficiency. © 2024 ieee.

关键词： Solar energy

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Accelerating the Multi-Objective Optimization of Crystallization Process using High Fidelity Population Balance Model Under NUMBA CUDA Environment 10

Accelerating the Multi-Objective Optimization of Crystalliza...

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10th Indian control conference, ICC 2024

作者： Rangavajhala, Anirudh Tadepalli, Aswitha Mitra, Kishalay Dept. of Chemical Engineering Indian Institute of Technology Hyderabad Telangana Hyderabad India

ISBN: (纸本)9798331517212

Crystallization is one of the majorly used separation techniques owing to its high efficiency and ease of operation. The optimization of the crystallization process involves the high-fidelity population balance models, thereby significantly increasing the computational complexity. This study, therefore, explores the acceleration of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) using NUMBA CUDA for multiobjective optimization for crystallization of ortho-amino benzoic acid. By harnessing GPU parallel processing, significant reductions in computation time are achieved, particularly for large populations and complex optimization problems. The GPU-accelerated NSGA-II algorithm in the optimization of ortho amino benzoic acid crystallization demonstrates significant performance boost by reducing the time by 122 times without any reduction in the solution quality. This research, therefore, underscores the potential of GPU acceleration in evolutionary algorithms and sets the stage for further advancements in high-performance parallelized optimization techniques, promising significant improvements in real-time optimization scenarios. © 2024 ieee.

关键词： Genetic algorithms

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