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4th IEEE international conference on Advance computing and Innovative Technologies in engineering, ICACITE 2024

作者： Goyal, Shweta Shankar, Amalraj Das, Kailash Chandra Singh, Akhilesh Oli, Sanjay Sati, Madan Mohan Graphic Era Deemed to Be University Dept. of Electrical Engineering Dehradun India Kj College of Engineering & Management Research Dept. of Electrical Engineering Pune India G H Roisoni University School of Engineering & Technology Maharastra Amravati India Vmsb Uttarakhand Tech. University Department of Electrical Engineering Pithoragarh262502 India Dayananda Sagar College of Engg Department of Mathematics Bangalore560078 India Graphic Era Hill University Deptt. of Mathematics Bhimtal263136 India

ISBN: (纸本)9798350360165

PID controllers have proven to be critical to company operations, enabling precise control of a variety of components. In addition, several PID control algorithms have been developed to facilitate the implementation of the system and improve response. However, the manual tuning process faced problems, such as reduced accuracy and long response time. Several automatic PID tuning techniques have been developed to solve this control problem. Adaptive Tuned PID is one of the most common methods for accurately and correctly tuning plant outputs to predetermined locations. In order to simulate a typical paperwork, this work aims to develop a laboratory scale prototype of an adaptive tuned PID controller to balance the shaft with the rotor Hardware implementation of the idea that creates the PID uses an Arduino Uno microcontroller loaded with several algorithms for three situations: manually tuned PID with constant value, hand tuned PID with various inputs via potentiometer, and LabVIEW Virtual to determine the output of adaptively tuned PID controllers Data a in this case enter and graphs are created. Several transient response characteristics of the identified laboratory model, including large overshoot, peak time, peak time, maximum, delay, and maintenance time is shown in the results The software of the planned model for both manual and adaptive tuned PID controllers is also built using MATLAB Simulink. A comparison of the two controllers is shown last. © 2024 IEEE.

关键词： Three term control systems

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automatic Qubit Characterization and Gate Optimization with QubiC

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ACM TRANSACTIONS ON QUANTUM computing 2023年第1期4卷 1-12页

作者： Xu, Yilun Huang, Gang Balewski, Jan Morvan, Alexis Nowrouzi, Kasra Santiago, David I. Naik, Ravi K. Mitchell, Brad Siddiqi, Irfan Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Univ Calif Berkeley Berkeley CA 94720 USA

As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration techniques require complicated and verbose measurements to tune up qubits and gates, which cannot easily expand to the large-scale quantum systems. We develop a concise and automatic calibration protocol to characterize qubits and optimize gates using QubiC, which is an open source FPGA (field-programmable gate array)-based control and measurement system for superconducting quantum information processors. We propose multi-dimensional loss-based optimization of single-qubit gates and full XY-plane measurement method for the two-qubit CNOT gate calibration. We demonstrate the QubiC automatic calibration protocols are capable of delivering high-fidelity gates on the state-of-the-art transmon-type processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. The single-qubit and two-qubit Clifford gate infidelities measured by randomized benchmarking are of 4.9(1.1) x 10(-4) and 1.4(3) x 10(-2), respectively.

关键词： FPGA gateware quantum gate calibration qubit control NISQ engineering software

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Optimize ISAR Imaging Techniques for Diverse Moving Targets 4

Optimize ISAR Imaging Techniques for Diverse Moving Targets

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4th IEEE international Maghreb Meeting of the conference on sciences and Techniques of automatic control and Computer engineering, MI-STA 2024

作者： Elgadi, Yahya Abdulgader Emhemmed, Adel Saad Aref, Ibrahim Asaad Univerversity of Tripoli Electrical and Electronic Engineering Departement Tripoli Libya School of Computing and Communications Lancaster University Lancaster United Kingdom

ISBN: (纸本)9798350372632

ISAR has emerged as a powerful tool within radar technology, specifically designed for imaging and analyzing moving targets. Unlike conventional radar systems, ISAR leverages the motion of the target itself to create high-resolution images. This work explores the methodology and implementation of ISAR imaging, with a specific emphasis on both simple and complex objects, including cubes, spheres, and aircraft. The study investigates three distinct cases, examining the impact of optimum design procedures, variations in center frequency, and alterations in resolution. The main objective of this paper is to optimize ISAR imaging techniques for diverse moving targets, highlighting the importance of adhering to best practices in radar system design. The study demonstrates the effectiveness of optimum design procedures in achieving high-fidelity ISAR images. The results underscore the critical role of resolution in capturing precise and informative ISAR images, providing valuable insights for future advancements in radar technology and imaging systems for moving targets. © 2024 IEEE.

关键词： Radar imaging

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High Speed Neural Network MPPT Algorithm for DFIG Based Wind Energy Conversion System 7

High Speed Neural Network MPPT Algorithm for DFIG Based Wind...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Tharwin Kumar, R. Balaji, V. Sakthidhasan, K. Gomathi, S. Sreedhar, R. Janaki, N. Puducherry Technological University Department of Electrical and Electronics Engineering Puducherry India MAI-NEFHI College of Engineering and Technology Faculty of Electrical and Electronics Engineering Asmara Eritrea Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Electrical and Electronics Engineering Chennai India St. Joseph's College of Engineering Department of Electrical and Electronics Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350372816

For the generation of electrical energy, breeze energy is a trustworthy and talented renewable vitality basis. An innovative proposal with many scientific and economic benefits is using wind source technology to charge electric vehicles. Worldwide, the market for Wind Energy Conversion System (WECS) has been expanding significantly. High-quality output power is commonly produced when wind energy demand grows. WECS has significant modelling, control, and grid integration issues as a result of the intermittent nature of wind energy. A proper controller mechanism has to be created in order to significantly improve WECS. An innovative method for maximizing the power of wind energy founded on Radial Basis Function Neural Networks (RBFNN) is proposed in this study to increase the power of Double Fed Induction Generators (DFIG). DFIG based wind turbine, and to provide outstanding dynamic performance in response to breeze rapidity fluctuations. MPPT is a strong algorithm that operates around an ideal rotating speed by utilizing RBFNN for mechanical speed control. We evaluated the performance of DFIG founded WECS with MATLAB/Simulink. The RBFNN efficiency is 91% when comparing MPPT controllers. © 2024 IEEE.

关键词： Radial basis function networks

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Intelligent Curtain System Based on MCGS and PLC 3

Intelligent Curtain System Based on MCGS and PLC

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2023 IEEE 3rd international conference on Data science and Computer Application, ICDSCA 2023

作者： Weiqi, Luo Meijun, Liu Xiamen University of Technology School of Electrical Engineering and Automation Xiamen China

ISBN: (纸本)9798350341546

Nowadays, more and more intelligent electrical appliances will replace the ' old electrical appliances ' in our life. Many intelligent electrical appliances have been realized and entered our daily life. This article is mainly aimed at the design and description of intelligent curtains in intelligent electrical appliances. The market of intelligent curtains is also very broad, and both the application prospect and the market prospect have great potential value. The intelligent curtain designed in this paper realizes automatic or manual switch control of the curtain to control the adjustment of indoor brightness. The curtains are provided with multiple layers to adjust the brightness, softness and darkness of the indoor light. © 2023 IEEE.

关键词： automatic control curtain intelligent electrical appliances layered control motors and electrical appliances

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Don’t Train, Just Prompt: Towards a Prompt engineering Approach for a More Generative Container Orchestration Management 14

Don’t Train, Just Prompt: Towards a Prompt Engineering Appr...

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14th international conference on Cloud computing and Services science, CLOSER 2024

作者： Kratzke, Nane Drews, André Department of Electrical Engineering and Computer Science Lübeck University of Applied Sciences Germany Expert Group Artificial Intelligence in Applications Lübeck University of Applied Sciences Germany

ISBN: (纸本)9789897587016

Background: The intricate architecture of container orchestration systems like Kubernetes relies on the critical role of declarative manifest files that serve as the blueprints for orchestration. However, managing these manifest files often presents complex challenges requiring significant DevOps expertise. Methodology: This position paper explores using Large Language Models (LLMs) to automate the generation of Kubernetes manifest files through natural language specifications and prompt engineering, aiming to simplify Kubernetes management. The study evaluates these LLMs using Zero-Shot, Few-Shot, and Prompt-Chaining techniques against DevOps requirements and the ability to support fully automated deployment pipelines. Results show that LLMs can produce Kubernetes manifests with varying degrees of manual intervention, with GPT-4 and GPT-3.5 showing potential for fully automated deployments. Interestingly, smaller models sometimes outperform larger ones, questioning the assumption that bigger is always better. Conclusion: The study emphasizes that prompt engineering is critical to optimizing LLM outputs for Kubernetes. It suggests further research into prompt strategies and LLM comparisons and highlights a promising research direction for integrating LLMs into automatic deployment pipelines. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Automation

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Edge computing for Microgrid via MATLAB Embedded Coder and Low-Cost Smart Meters 8

Edge Computing for Microgrid via MATLAB Embedded Coder and L...

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8th international conference on Smart Grid and Smart Cities, ICSGSC 2024

作者： Xu, Linna Huang, Jian Yang, Shan Zhu, Yongli School of System Science and Engineering Sun-Yat Sen University Guangzhou China

ISBN: (纸本)9798350377408

In this paper, an edge computing-based machine-learning study is conducted for solar inverter power forecasting and droop control in a remote microgrid. The machine learning models and control algorithms are directly deployed on an edge-computing device (a smart meter-concentrator) in the microgrid rather than on a cloud server at the far-end control center, reducing the communication time the inverters need to wait. Experimental results on an ARM-based smart meter board demonstrate the feasibility and correctness of the proposed approach by comparing against the results on the desktop PC. © 2024 IEEE.

关键词： MATLAB

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Printed Circuit Board Defect Detection Using CNN Based Deep Learning Technique 4

Printed Circuit Board Defect Detection Using CNN Based Deep ...

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4th international conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Bardia, Viksith Prabu, M. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387490

Being in the competitive area of electronics manufacturing, PCB defects have to be detected for reliability of products and maintaining the quality standards. This paper deals with the new advanced methodology for PCB automatic inspection by using CNN-based methodology for the detection of defect on PCBs. The models were highly trained and tested with a huge dataset that was designed especially for the identification of defects in PCBs. For effective identification and classification of various defects like the irregularities, missing components, gaps and electrical shorts, this paper uses the CNN architecture. The achieved results of experiments with the model's accuracy up to 95.57%, precision up to 95.44% and recall up to 93.76% underscore the importance of achieving high performance. Ensuring such stable and accurate representation of the CNN - based method makes this approach valuable in improving the production workflow. This automatic defect detection system enables man inspection to be minimized. Hence the possibility of human error becomes low and thus forms a reliable solution for production efficiency improvement and strict quality control throughout the electronics manufacturing process by the manufacturers. © 2024 IEEE.

关键词： Inspection

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Cloud Based Automated control System Workshops and Rooms for controlling Parameters 1

Cloud Based Automated Control System Workshops and Rooms for...

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1st international conference on Advances in Computer science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kumar, Dinesh Kuntal, Ravinder Singh Deep, Pragya Chamoli, Anup Shekhar Singh, Pinki Mandal, Rishabh SRM Institute of Science & Technology Department of Computer Science and Engineering UP Ghaziabad India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India IIMT College of Engineering Department of AI & DS Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun248001 India Accurate College of Engineering & Management Department of Computer Science and Engineering Greator Noida India Tula's Institute Department of Computer Science and Engineering UK Dehradun India

ISBN: (纸本)9798331518578

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing. © 2025 IEEE.

关键词： Smart manufacturing

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A Novel Cutting Fluids Performance Assurance System for CNC Machine Tools

A Novel Cutting Fluids Performance Assurance System for CNC ...

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2024 international automatic control conference, CACS 2024

作者： Chou, You-Syuan Chen, Yi-Shiang Chiang, Fu-Yu Yang, Chen-Yen Shi, Zhe-Xun Lin, Yu-Sheng Lin, Shang-Chih Su, Shun-Feng Huang, Yennun Feng Chia University Institute of Automatic Control Engineering Taichung407 Taiwan Feng Chia University Department of Automatic Control Engineering Taichung407 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei115 Taiwan

ISBN: (纸本)9798350354904

In the CNC machine tool industry, cutting fluid is a crucial component of the machining process. Nevertheless, as the duration of cutting fluid use increases, its performance progressively deteriorates, presenting a significant challenge that necessitates resolution. This study introduces an innovative intelligent monitoring system designed to optimize the preparation of cutting fluid in CNC machine tools. The aim is to extend the fluid's service life, mitigate tool wear, and address issues arising from fluid degradation. The system integrates a heating plate, sensors, pumping motors, and embedded systems to monitor and manage the cutting fluid effectively. Testing was conducted using a customdesigned container, and data analysis identified the optimal supply strategy, thereby extending the usable lifespan of the cutting fluid. This system enhances production longevity and allows for the configuration of containers with appropriate capacities based on specific requirements, ensuring consistent and high-quality production. © 2024 IEEE.

关键词： Cutting fluids

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