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2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Kleimenkin, Dmitriy V. Pakhomov, Ilya V. Denisenko, Darya Y. Don State Technical University Dept. of Scientific Research Dept. of Information Systems and Radio Engineering Rostov-on-Don Russia Don State Technical University Dept. of Scientific Research Dept. of Instrumentation and Biomedical Engineering Rostov-on-Don Russia Don State Technical University Dept. of Scientific Research Rostov-on-Don Russia Southern Federal University Dept. of Automatic Control Systems Rostov-on-Don Russia

ISBN: (纸本)9798350360646

The paper presents a promising method of increasing by more than an order of magnitude the maximum slew rate (SR) of integrated operational amplifiers (OpAmps) based on two-cycle 'folded' cascodes. This method is based on the introduction of special differentiating transient correction circuits into the classical circuits of OpAmps. Developed on the basis of the MH2XA031 array chip, the high-speed OpAmp is recommended for practical use in the subclass of so-called discrete-analog SC-filters on switched capacitors, for which (in some important cases) higher SR values are required. The effect of significantly improving the OpAmp's speed is to provide higher output current levels of the two-cycle 'folded' cascode that recharges the integrating correction capacitor during the transient edge. The OpAmp's speed performance in the large-signal mode is increased from 248.7 ~V / μ s to 4148 ~V / μ s as a result of this. © 2024 IEEE.

关键词： BJT GaAs high-temperature chips high-temperature integrated resistors nJFET operational amplifier

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Optimization of PID controller based on various tuning methods

Optimization of PID controller based on various tuning metho...

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2023 International Conference on Power, instrumentation, Energy and control, PIECON 2023

作者： Singh, Siddharth Singh, Vijander Rani, Asha Yadav, Jyoti Netaji Subash University of Technology Dept. of Electrical Engineering Dwarka Sector-3 New Delhi India Netaji Subash University of Technology Dept. of Instrumentation and Control Engineering Dwarka Sector-3 New Delhi India

ISBN: (纸本)9798350399769

PID controllers have been in use for numerous decades. Many researchers have developed and discussed their tuning methods. In this presented work, we discuss different types of tuning methods for Proportional Integral Derivative (PID) controllers. The present work also discusses about plants with delay time and their equivalent First Order Plus Time Delay (FOPDT) structure with their tuning method. Furthermore, a two-degree of freedom (2-DOF) PID controller and its tuning methods have also been discussed. Lastly, Genetic Algorithm (GA) has been employed so as to optimally tune the PID controller. The tuning methods for PID controllers have been tested. The simulations are carried out in MATLAB Simulink (2020a). The results are then recorded in tabular form and compared with classical tuning methods present in literature. Finally, the best tuning method out of the discussed methods for the plant has been concluded. © 2023 IEEE.

关键词： Genetic algorithms

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Agrobot for Inter-Row and Intra-Row Weeding

Agrobot for Inter-Row and Intra-Row Weeding

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Mugdha Jog Sudhir Agashe Dept. of Instrumentation and Control Engineering COEP Technological University Pune India

Strengthening the backbone of small farmers by developing small-sized automated machines will strengthen India as labour is scarce nowadays. Weeds are undesirable plants in a farm that substantially reduce crop yield and quality. Farmers often spend a lot of resources to reduce their impact unsuccessfully. Weed control costs 33% of the total cost of cultivation. Though intra-row weeds are 25% and inter-row weeds are 75% of the total weeds present on the farm, intra-row weeds are more dangerous than inter-row weeds. Also, they are difficult to remove. The proposed autonomous weeder is a prototype model that operates on a rechargeable electric battery. While going through a row, weeds are removed between two rows by flat and sharp blades (inter-row operation) on both sides. Simultaneously photos of space between two crops in one row are captured by the camera. Image processing and classification are done using Raspberry Pi, a machine learning model, and artificial intelligence. The detected weeds are removed by flat and sharp blades weeding tool attached to the mechanical linkage centrally (intra-row operation). Raspberry Pi is also used for controlling the pneumatic actuator, and motor. Testing of the machine in farms is in progress.

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Design and Simulation of Self-tuning PID controller with MPPT for Solar Array using MATLAB/Simulink 13

Design and Simulation of Self-tuning PID controller with MPP...

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13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Shinde, Amar B. Deshpande, Amruta S. Unde, Snehal College of Engineering Pune Dept. of Instrumentation and Control Pune411 005 India College of Engineering Pune Dept. of Electrical Engineering Pune411 005 India

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

The photovoltaic (PV) system's nonlinear nature, uncertainty in temperature, and light intensity in the environment are responsible for the fluctuation of the maximum power point (MPP). Many maximum power point tracking (MPPT) algorithms are proven effective in the literature, including use of artificial intelligence. Proportional integral derivative controller and fuzzy controllers found effective to track MPP. Using the combination of Fuzzy-PID controller, swiftly adapt to changes in the atmosphere to confirm the solar array is continually operating at its highest efficiency with MPP. Easy and effective oscillation elimination is possible with PID control. To regulate the maximum power of the PV system combination of Fuzzy-PID self-tuning controllers is found *** goal is to enhance a PV system's dynamic response to in presence of irradiation and temperature fluctuations. For tuning Fuzzy logic controller (FLC), gain scheduler values of the proportional, integral, and derivative constants are fundamental. The design processes for non-linear conventional PID controllers, FLC, and series combination of Fuzzy-PID controller are discussed. It compares the traditional PID controller, FLC, and Fuzzy-PID controller. The comparison of outputs produced for PID, FLC, and series Fuzzy-PID controller confirms the effectiveness of the algorithm. Use of Fuzzy controller helps in self-tuning of PID controller constant value. MATLAB/Simulink based environment used to perform the simulations. © 2022 IEEE.

关键词： Three term control systems

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A Study On Suitable Electrodes For Low-Energy Power Generation From Carbon Waste in Factories

A Study On Suitable Electrodes For Low-Energy Power Generati...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Channgamthiang, Surasak Nusukhon, Pheeraphat Chansri, Pakpoom King Mongkut's University of Technology Thonburi Dept. Electrical Technology Education Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9798350332360

Factory waste includes the incomplete combustion of industrial fuels that causes carbon to precipitate in vents. These carbons might be put to good use. Therefore, the impact of using waste carbon in factories to produce electricity is investigated in this study by evaluating electrical characteristics: the type of electrode material's suitability, the size of the electrode's carbon contact surface area, and the distance between the electrodes. According to the findings, the maximum open circuit voltage (Voc) was 1.09 V for copper (+) and zinc (-) electrode materials, 1.11 V for the electrode's carbon contact surface area, and 1.29 V for the electrodes' spacing. The maximum of Voc was 1.11 V, maximum on-load voltage and current were 0.64V, 124.65 mA for optimum electrode carbon contact surface size 40 cm2. Optimum electrode distance at 2 cm that maximum open circuit voltage (Voc) was 1.29 V. The maximum load voltage and current were 0.77V, 128.32mA. Factory waste carbon can be useful in some applications for producing electricity from waste carbon and assisting in the reduction of factory waste. © 2023 IEEE.

关键词： Carbon

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OBJECT DETECTION AND LANE CHANGING FOR SELF DRIVING CAR USING CNN

OBJECT DETECTION AND LANE CHANGING FOR SELF DRIVING CAR USIN...

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2022 International Conference on Communication, Computing and Internet of Things, IC3IoT 2022

作者： Saranya, M. Archana, N. Reshma, J. Sangeetha, S. Varalakshmi, M. Psg College of Technology Dept. of Instrumentation & Control Systems Engineering Coimbatore India Psg College of Technology Dept. of Electrical & Electronics Engineering Coimbatore India

ISBN: (纸本)9781665479950

In recent years, many companies are working on the development of autonomous cars. Every citizen on the planet is concerned about their safety. In the framework of Advanced Driver Assistance Systems, one of the main goals is to improve safety and reduce road accidents, ultimately saving lives. One of the most difficult jobs in an autonomous driving system is detecting road lanes or road boundaries. Lane and object detection may be a crucial component of collision prevention in driving assistance systems. With the growth in traffic, there is a demand for more security and comfort when driving, it impose the development of new technology. Computer vision is one of the ways that may be utilized to assist the driver in difficult scenarios in order to improve his safety and comfort. The initial layer of autonomous vehicles' capabilities is lane tracking. Many sensors, including as lasers, radar, and vision sensors, are commonly employed for obstacle and lane detection. Computer vision is one of the primary method for detecting road limits and lanes using a vehicle's vision system. The technology uses a camera installed on the vehicle to capture the front view, then uses a few algorithms to detect lanes and objects. The lanes and objects are detected using a flexible algorithm. This paper focuses on a computer vision-based object detection technique by using CNN algorithm. © 2022 IEEE.

关键词： Object detection

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Study on Deep Reinforcement Learning for Mobile robots Flocking control in Certainty Situations 19

Study on Deep Reinforcement Learning for Mobile Robots Flock...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Kheawkhem, Pontakorn Khuankrue, Issarapong King Mongkut's University of Technology Thonburi Dept. of Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Mobile robots are the widely used machines that will be a part of life. It can easily be scaled to meet the requirements of human uses and can move to different target areas freely. However, mobile robots have a problem with mobility, which needs to respond to human activities and obstacles. Reinforcement learning (RT) is a part of machine learning, which enables the machine to learn by themselves. It can develop in a real-world environment without machine teaching or patterns. This paper proposed the study on the flocking control simulation, which avoids the obstacles. Mobile robots in simulation presented by using Multi-Agent Deep Deterministic Policy Gradient (MAD-DPG). The proposed algorithm, the deep reinforcement learning algorithm, is the main navigation of robots, which find the target, maintain distance between robots, and avoid collision with obstacles by learning features and characteristics with certainty environment, obstacle, robots, and target. On the simulation, the authors operate all of the positions in the environment, and robots speed in the environment as the state. © 2022 IEEE.

关键词： Reinforcement learning

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Development of Real-Time Oxygen and Temperature Monitoring System with CI/CD Pipeline Integration and HMI

Development of Real-Time Oxygen and Temperature Monitoring S...

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Gaurav Amar Kolte Aditya Gunnal Nilima R. Kolhare Dept. of Electronics and Telecommunication Engineering COEP Technological University Pune Dept. of Instrumentation and Control Engineering COEP Technological University Pune

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

The steel manufacturing industry stands as the backbone of global infrastructure development, providing the raw materials essential for constructing everything from skyscrapers to automobiles. Central to this industry's efficiency is the performance of its furnaces, where the transformation of raw materials into high-quality steel occurs. Steel furnace environments require precise monitoring of parameters like temperature and oxygen levels to ensure efficiency, safety, and compliance with environmental standards. This paper presents a novel monitoring device designed to address these needs while incorporating modern software development practices. The device offers real-time monitoring and graph visualization of temperature and oxygen levels, surpassing conventional methods. It introduces the integration of Git, Continuous Integration/Continuous Deployment (CI/CD) pipelines, Real-Time Operating Systems (RTOS) and diagnostic tools, enhancing reliability and facilitating seamless updates. This amalgamation of hardware and software engineering replaces outdated monitoring systems. Through its multifaceted capabilities, this research contributes significantly to the evolution of smart, interconnected industrial systems, promising improved performance and safety in steel furnace operations. The NXP LPC 55s69 micro-controller unit is used for the computation of oxygen and temperature from a zirconia-based oxygen sensor and thermocouple using nernst-einstein equation. For integration of the device with a PLC control we have used RS232 and RS485 communication protocols.

关键词： Temperature measurement Performance evaluation Oxygen Furnaces Pipelines Real-time systems Raw materials Safety Steel Monitoring

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Traffic Speed Limit Sign Recognition using Deep Learning 7

Traffic Speed Limit Sign Recognition using Deep Learning

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Kamali, B. Kishore, A. Rajkumar, S. Saravanakumar, K. Dhanaselvam, J. Rajesh, R. Sri Krishna College of Technology Dept of Instrumentation And Control Engineering Tamilnadu Coimbatore India Sri Krishna College of Technology Dept. of Electrical And Electronics Engineering Tamilnadu Coimbatore India Indian Institute of Technology Madras Department of Engineering Design Tamilnadu Chennai600036 India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359299

Automated interpretation of data from roadside traffic signs is extremely helpful for road surveying, autonomous vehicle applications, and enhancing road infrastructure and safety. However due to the high degree of sign similarity, low visibility, and unfavorable nature condition of the road environment, this is a very difficult challenge. In the present research, an approach for automatic detection and recognition of speed limit based on an improved version of YOLOv5n was developed to address the issues in the traffic speed limit sign recognition system, the typical target detection algorithm has low recognition accuracy, sluggish rate, disregarded detection, and inaccurate detection. Deep learning algorithms can extract speed limit data from Roadside automatically. There are two approaches to introduce this method. First of all, it is suggested to partition speed limit signs into one class based on their pixels rather than grouping each sign into a different class. A second proposal is a classifier that can differentiate between speed signs and non-speed signs by evolving its weights, utilizing a false alert class. Images of all of India's state highways were used for developing the data set. The suggested method is very accurate in identifying and detecting speed limit signs, according to the comparative study of the data. The suggested method, with a processing time of 0.040 seconds per frame, produced an average recognition accuracy of 90% using YOLOv5n. This quick calculation time improves system reliability and stability in real-time applications. © 2024 IEEE.

关键词： Roadsides

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Comparative performance analysis of intelligent controllers for solar tracking system

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Materials Today: Proceedings 2022年 65卷 3731-3740页

作者： Singh, Amit Kumar Chauhan, Yamini Sharma, Navneet Dept. of Instrumentation and Control Dr. B.R. Ambedkar National Institute of Technology Jalandhar Punjab 144011 India Government Engineering College Bharatpur 321001 India

Solar Energy is the cleanest, cheapest and the most abundant form of renewable energy source that could complement the conventional fossil fuels but the continuous change in the position of the sun relative to earth reduces the power produced by it. In order to overcome this problem, solar tracking system are used to increase the efficiency of the photo voltaic panel. The conventional PID controllers are used for controlling linear and negligible lag system. For controlling non linear system the conventional controllers does not work effectively, therefore for such system intelligent control techniques are needed. This paper elucidates the performance comparative analysis of three intelligent controllers based on Artificial Neural Network which are Model Predictive controller, Nonlinear Auto Regressive Moving Average (NARMA-L2) controller and Adaptive-Network-Based Fuzzy Inference System (ANFIS) controller. The simulation of the above controllers are done using MATLAB/ SIMULINK. © 2022

关键词： controllers

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