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8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Kadu, C.B. Gawali, A.R. Bhosale, V.P. Vikhe, P.S. Pravara Rural Engineering College Department of Instrumentation & Control Engineering MS Loni India

ISBN: (纸本)9798350334012

In the area of control system, main objective is to ensure stability of process and minimize losses. Most industrial systems suffer from issue of slow operation or delayed operation due to input delay. In this study an operational scheme is developed to keep the process status within permissible delay limits. A controller for rejection of disturbance based on prediction is realized in sample time discrete form. The design is functional for steady state open-loop and uncertain systems. The deterministic states of system are estimated using extended state observer (ESO). The filter smith predictor is used to ensure output response free from delay and guarantee stability of the system with uncertainty and external disturbances. The simulation results of higher order systems are presented and compare with conventional control. © 2023 IEEE.

关键词： Disturbance rejection

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Wireless Crawling of Inchworm-Like Robot by Induction Heating 22

Wireless Crawling of Inchworm-Like Robot by Induction Heatin...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Jung, Woojun Lee, Seonghyeon Hwang, Yongha Korea University Department Of Control And Instrumentation Engineering Korea Republic of

ISBN: (纸本)9784886864352

Bio-inspired micro/nano-scale robots with various soft materials and operation mechanisms are being extensively reported. One of the challenges for soft robots is to be untethered and lightweight. This study developed a tiny soft robot that moves wirelessly, while also being biocompatible. Because the robot has a built-in magnetic composite, energy is transferred by induction heating in a magnetic field. The robot utilizes frictional hysteresis in its two legs and explosive gas pressure generated by a magnetic composite heater to move forward. The robot's soft body can move up to 22% of its length by expansion and contraction. © 2023 IEEJ.

关键词： 3D Printing Composite Heater Induction Heating Soft Robot Wireless Operation

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Harvestgo-A Versatile Weed Identifier Using AI

Harvestgo-A Versatile Weed Identifier Using AI

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2023 Intelligent Computing and control for engineering and Business Systems, ICCEBS 2023

作者： Ilayaraja, R. Harini, S. Kathiravan, S. Aishwariya, A. Sri Sai Ram Engineering College Department of Instrumentation and Control Engineering Chennai India

ISBN: (纸本)9798350394580

In today's world, everywhere needs technological development so that the work can be done simultaneously to get good results. In the future, automation will dominate all areas, especially agriculture. Most problems are caused by vegetation surrounding the plants and preventing them from growing. The aim of the project is to create an artificial intelligence-supported weed detection and removal system for coconut farms. We use image processing and sensing tools to install TENSOR-FLOW-based AI models on inexpensive hardware such as Raspberry Pi. The technology instantly collects images, detects weeds growing on coconut trees, and initiates the necessary cleaning process while preserving the coconut plants. Our approach is to improve weed control strategies, increase coconut yields, and improve agricultural sustainability through agricultural automation. The report describes the process, hardware configuration, artificial intelligence model development, and live operation, demonstrating the project's efficiency and productivity potential in agriculture. © 2023 IEEE.

关键词： Raspberry Pi TensorFlow-Based Model Weed Management

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Particle Swarm Optimization Tuned PID control of Hybrid Renewable Energy Based Multi-Area Power System

Particle Swarm Optimization Tuned PID Control of Hybrid Rene...

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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Gulzar, Muhammad Majid Shahab, Muhammad Shakoor, Adnan Department of Control & Instrumentation Engineering Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350304602

The hybrid power system combines renewable and conventional power plants, resulting in certain power quality issues such as longer settling times and increased transient contents. One of the most significant problems with such a hybrid system is frequency variations, which can affect the overall efficiency and reliability of the energy system. To address this concern, the Load Frequency controller (LFC) is used to sustain the system frequency within safe limits and ensure the efficient and reliable operation of the electric grid. The primary function of governing the oscillation of load is to adjust the power delivery and balance the load demand of the system to maintain a specific range of power output. This study tries to determine the best control approach for efficiently regulating system frequency and upholding a power balance in the presence of renewable energy sources. In this work, controllers such as Proportional Integral Derivative (PID), Genetic algorithm-PID (GA-PID), and Particle Swarm Optimization-PID (PSO-PID) are examined and studied to settle the load oscillation issue arising in a two-area energy generation system. Comparison of results obtained with the controllers are presented and summarized based on their settling time (Ts), maximum overshoot (%OS) oscillation, and steady-state error (SSE). © 2023 IEEE.

关键词： controllers

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Smart Dosing: Harnessing AI for Alum dosage Predictions in Water Treatment

Smart Dosing: Harnessing AI for Alum dosage Predictions in W...

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2023 Intelligent Computing and control for engineering and Business Systems, ICCEBS 2023

作者： Mohanraj, K. Madhumita, S. Harini, M. Rohind Praveen Raj, S. Balaji, N. Jayanthi, G. Sri Sai Ram Engineering College Department of Instrumentation and Control Engineering Chennai India

ISBN: (纸本)9798350394580

Water treatment methods, such as coagulation, flocculation, and sedimentation, play a crucial role in maintaining water quality. However, these methods encounter limitations due to the increasing pollution stemming from household, agricultural, and industrial waste. In response to this issue, our study delves into the exploration of advanced machine learning algorithms (SVM, MLR, RFR) for a comprehensive analysis of water. The findings from our research contribute to the development of an innovative laboratory treatment plant designed to mitigate the environmental impact caused by water pollution. © 2023 IEEE.

关键词： agricultural waste coagulation environmental impact flocculation household waste industrial waste laboratory treatment plant machine learning algorithms MLR pollution RFR sedimentation SVM water treatment

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Design A Smart Pillow for Detection and Management of Snoring 8

Design A Smart Pillow for Detection and Management of Snorin...

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8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Agawane, Aishwarya Mudhalwadkar, Rohini College of Engineering Pune Instrumentation and Control Department Pune India

ISBN: (纸本)9798350334012

Snoring is one of the most common disorder and yet there is no proper solution for this problem. Polysomnography test is required to have before using any kind of snoring devices. So, the work is focused on a system which help to detect snoring and to manage snoring by alerting that patient. A multi-sensor system is designed so that it will sense, record and alert by using an Internet of things platform. Thus system helping patients to have a good quality of sleep because it has inbuilt music system which play relaxing music when required, meanwhile the patient snores then the system will alert that patient. One of the effect of snoring is neck pain, so an attempt is made to provide neck pain solution into pillow by considering some biological aspects. This system also gives support to neck , back and the head of the patient. © 2023 IEEE.

关键词： Internet of things

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Relief Facility Locations Using P-median Weight Minimax Model

Relief Facility Locations Using P-median Weight Minimax Mode...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Ayudhya, Wichitsawat Suksawat Na Instrumentation and Control Engineering Department School of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10250 Thailand

ISBN: (纸本)9798350386097

Thailand's eastern seaboard is the fastest growing area because of several export economic zones. However, this region historically encountered flood problems because of the Monsoon season and urbanization. To be proactive, the authority must plan to locate relief facilities in advance. Hence, we deployed the P-median weight Minmax model with historical population data in flood areas to decide the relief facility locations. We also investigated three contingency plans where 1) we determined relief facilities from our model, 2) we assigned the number of relief facilities according to the population, and 3) we investigated the contingency plan to determine alternative relief locations when some districts are not suitable. We tested our model with 2015, 2016, 2017, 2018, and 2019 data. © 2024 IEEE.

关键词： Supply chain management

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Auto tuned PID and neural network predictive controller for a flow loop pilot plant

Auto tuned PID and neural network predictive controller for ...

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作者： Patil, Sanjay R. Agashe, Sudhir D. Department of Instrumentation and Control Engineering College of Engineering Pune MS Pune411005 India

This paper presents an advanced control strategy that uses the neural network (NN) predictive controller to govern the dynamics of a Flow loop pilot plant. The set point tracking using NN Predictive controller and conventional PID strategies are investigated. The control objective is to keep the outlet flow of the Single Input Single Output Flow loop at a reference value. An orifice meter as a flow measuring device and Variable Frequency Drive as a final control element is selected to collect Input, Output data. System Identification toolbox in MATLAB is used to construct the model of a flow loop from measured input–output data. Various models are estimated, validated and realized that the transfer function model gives the best fit. This model is used to build the PID and NN Predictive controller. NN predictive controller parameters are set, by the designer's expertise. The performance of a NN predictive controller is then compared with the conventional auto-tuned PID controller. Experimental results are presented, which emphasizes the superiority and effectiveness of the NN predictive controller. © 2022

关键词： Pilot plants

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Optimal MBU Positioning under Fault Scenario for Distribution Networks with high PV Penetration 14

Optimal MBU Positioning under Fault Scenario for Distributio...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Caruana, Cedric Bhattacharya, Somesh Raute, Reiko Micallef, Alexander Scerri, Kenneth Department of Electrical Engineering Faculty of Engineering University of Malta Msida Malta Department of Systems and Control Faculty of Engineering University of Malta Malta

ISBN: (纸本)9781837242689

Faults on distribution networks due to abnormal weather events can lead to disruption and can cause high socio-economic losses. In line with the rising frequency of such events, the paper proposes an algorithm for the optimal deployment of mobile battery units to restore sections of the network. The considered battery units are rated at 1MVA to keep them realistic for the mobile application. The placement algorithm is formulated as a mixed integer mathematical optimisation problem. Sectionalising/tie switches are assumed on each branch of the network in order to increase the restoration configuration flexibility. Photovoltaic systems, distributed along the network, are allowed to contribute to the restored network sections. A number of critical loads are defined and these are prioritised in the restoration process. The objective function also considers the reduction of the overall renewable energy curtailment. The performance of the algorithm is tested on the IEEE 33 bus network with four tie lines. Scenarios with increasing levels of PV power are considered and the effect of incorporating the PV power is studied. © The Institution of engineering & Technology 2024.

关键词： Mixed-integer linear programming

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Collision avoidance and routing based on location access (CARLA) of mobile robots

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Neural Computing and Applications 2025年第9期37卷 6401-6430页

作者： ElSayyad, Shimaa Ezzat Saleh, Ahmed I. Ali, Hesham A. Saraya, M.S. Rabie, Asmaa H. Abdelsalam, Mohamed M. Computers Engineering Department MISR Higher Institute for Engineering and Technology Mansoura Round Road Mansoura City35516 Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Dean of Faculty of Artificial Intelligence Delta University for Science and Technology Gamasa Mansoura Egypt Faculty of Engineering Mansoura National University Gamasa Mansoura Egypt

The paper introduces a new path-planning robotic system methodology called Collision Avoidance and Routing based on Location Access (CARLA) for use in critical environments such as hospitals and crises where quick action and saving human lives are vital. The main focus of our framework is on accuracy and fast responses, such as delivering tools or items in a specific area while avoiding collisions with other robots and obstacles. CARLA is designed to provide quick responses during emergencies, unlike most existing algorithms that are integrated into site control units or distributed among mobile robots on-site. By being loaded onto a remote server node rather than individual robots, CARLA helps to conserve the robots' capabilities, hardware resources, and power consumption. Additionally, our system utilizes cloud computing and Fog servers technology to improve data transmission times between the cloud and smart devices, especially for applications with strict timing requirements like emergency response. The Fog platform is also leveraged to enhance on-site access to real-time interaction and location-based services by bringing processing power closer to the robots from far-off Cloud servers. CARLA has various applications, such as in factories and warehouses, where mobile robots need to be selected and directed by a central control system remotely. The proposed framework consists of three main modules: Robot Knowledge Module, Robot Selection Module, and Route Reservation Module, which will all be discussed in detail in this paper. The results of simulations using this framework show that the robots have improved flexibility and efficiency in terms of computing paths and successfully fulfiling requests without colliding, compared to traditional methods used in similar scenarios. © The Author(s) 2025.

关键词： Mobile robots

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