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Determination of Optimal Checkpoint Intervals for Quintuple Modular Redundancy Real-Time Systems

Transactions of the Korean Institute of Electrical Engineers 2025年第3期74卷 506-515页

作者： Kwak, Seong Woo Yang, Jung-Min School of Electronics Engineering Kyungpook National University Korea Republic of Dept. of Control and Instrumentation Engineering Pukyong National University Korea Republic of

The paper proposes a novel checkpoint management method for a real-time system with a quintuple modular redundancy (QMR) structure wherein multiple fault detections are performed between checkpoints. If the detected faults can be overcome within the context of the QMR structure, they are recovered by simply synchronizing the state values. Otherwise, the system rollbacks to the most recent checkpoint and re-executes the task to recover from the faults. The real-time system having the QMR structure and incorporating the proposed checkpoint scheme is modeled by a Markov chain. Based on the Markov chain model, a probability equation is derived to calculate the likelihood of completing the real-time task within the deadline. The optimal number of checkpoints and fault detections maximizing the probability value are also determined. Numerical experiments are conducted to illustrate the optimization procedure of the real-time system with a QMR structure using the proposed checkpoint management method. Copyright © The Korean Institute of Electrical Engineers.

关键词： Markov processes

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Agrobot for Inter-Row and Intra-Row Weeding 6

Agrobot for Inter-Row and Intra-Row Weeding

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

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

ISBN: (纸本)9798350306613

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. © 2024 IEEE.

关键词： artificial intelligence autonomous weeder inter-row intra-row weeding machine learning

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Solar-Powered EV Charging and Adaptive Irrigation System

Solar-Powered EV Charging and Adaptive Irrigation System

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Kumar, Shashwat Miglani, Yash Tomar, Anuradha Netaji Subhas University of Technology Dept. of Instrumentation & Control Engineering New Delhi India

ISBN: (纸本)9798350364866

Solar photovoltaic (PV) irrigation systems are emerging as a promising technology for regions with high solar irradiance and unreliable grid electricity. However, their intermittent use necessitates capacity optimization. To address this issue, this paper proposes a solar-powered system that integrates adaptive irrigation and electric vehicle (EV) charging. In order to maximize utilization of energy depending upon the demand in real time, the system dynamically divides power from the PV array between an EV battery and an induction motor for irrigation. This study demonstrates that when the PV power decreases from 2.6 kW to 1.58 kW, the EV battery compensates by discharging approximately 1 kW. This illustrates how the EV battery adjusts for periods of lower PV output by transferring energy to the irrigation motor, guaranteeing continued optimal functioning. The irrigation system employs a fuzzy logic controller (FLC) to optimize water flow rate by adjusting rotor speed via the voltage-hertz (V/f) method, based on soil moisture and temperature. At 44°C and 50% soil moisture level, the FLC evaluates a reference synchronous speed of 1200 RPM to precisely align the water flow rate with soil requirements. This integrated approach addresses inefficiencies in the conventional PV irrigation model. The proposed system is validated through MATLAB Simulink®. © 2024 IEEE.

关键词： Soil moisture

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ML based Non-Invasive Diabetes Detection System using Pulse Decomposition Analysis of PPG Signal 8

ML based Non-Invasive Diabetes Detection System using Pulse ...

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8th International Conference on Signal Processing and Communication, ICSC 2022

作者： Shaan, Bhavya Yadav, Jyoti Prabha, Anju Dept. of Instrumentation and Control Engineering Delhi India Dept. of Instrumentation and Control Engineering Delhi India

ISBN: (纸本)9781665454308

In this paper, Pulse Decomposition Analysis (PDA) of Photoplethysmography (PPG) and physiological parameters is used to develop Non-Invasive (NI) Diabetes Detection system. For this study, dataset of 217 participants from normal, diabetes and prediabetes subjects are used. Further signals are segmented in 5sec window which is filtered using bandpass filter to remove noise. After filtration PDA features are extracted from PPG signal. A total of seven features are extracted. In addition to this physiological parameter such as age, weight and height of the participants are also used as features. For classification a matrix of (7886 times 10) is formed containing seven PPG features and three physiological parameters. Dataset is classified under three classes i.e., Diabetic, Pre-diabetic, and Normal. Two commonly known machine learning classification learning algorithm i.e., ensemble and decision Trees are used for classification. The results shows that 99.3% accuracy is obtained using ensemble tree method. The study shows feasibility of wearable device for non-invasive diabetes detection. © 2022 IEEE.

关键词： Decision trees

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Development of Real-Time Oxygen and Temperature Monitoring System with CI/CD Pipeline Integration and HMI 1

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

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1st International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kolte, Gaurav Amar Gunnal, Aditya Kolhare, Nilima R. COEP Technological University Dept. of Electronics and Telecommunication Engineering Pune411005 India COEP Technological University Dept. of Instrumentation and Control Engineering Pune411005 India

ISBN: (纸本)9798331518578

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. © 2025 IEEE.

关键词： Thermocouples

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New Environment Exploration Algorithm combining Bug, Free Segment and Turning Point Algorithm for Multi-robot System 9

New Environment Exploration Algorithm combining Bug, Free Se...

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9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023

作者： Abhishek, P. Potanpalli, Adarsh Pandey, Karnika Sridevi, V. National Institute of Technology Tiruchirappalli Dept. Instrumentation and Control Engineering Trichy India National Institute of Technology Tiruchirappalli Instrumentation and Control Engineering Trichy India

ISBN: (纸本)9798350334395

Exploration and mapping of an unknown environment is a challenging task and using a single robot is time consuming and inefficient. Multi robot System(MRS) is used to reduces exploration time as well as to cover larger areas and produces accurate maps. This work focuses on development of new environment exploration algorithm for multi robot system which combines the features of Bug, Free segmentation and turning point algorithms. The Proposed algorithm utilizes capabilities of three mobile robots and tested on simulated outdoor environment with static obstacles. Two sub robots are equipped with LiDAR sensors and are used to explore the region between initial and target location. The point cloud generated by LiDAR sensors of the two robots is shared with the main/mother robot to generate an occupancy map. Mother robot execute A∗ path planning algorithm on the occupancy map to find the shortest path and moves towards the target location. Proposed algorithm has low computational requirements and significantly reduces the time required to explore the given environment. Further, the performance of the proposed algorithm is compared with existing algorithms in terms of the time required to explore the environment and generate occupancy map. © 2023 IEEE.

关键词： Multipurpose robots

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Development of control for Low Flow Application 4

Development of Control for Low Flow Application

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Chikalthankar, Anagha N. Deshpande, Amruta S. Sonawane, Dayaram.N. Ghodinde, Ketaki A. Patil, Smita S. Coep Technological University Dept. of Instrumentation and Control Pune India Coep Technological University Dept. of Electronic and Telecommunication Engineering Pune India

ISBN: (纸本)9798350354218

Low-flow control applications are critical for shower systems and various industrial applications. These applications are indispensable due to the precise flow and temperature conditions required by many processes, which make them essential for achieving desired results. Present flow control applications vary in complexity, and some require skilled installation and maintenance, which can be expensive and sensitive. Traditional control methods can be limiting, resulting in heavy and bulky structures. This paper presents a novel mathematical modeling and advanced control strategy to control low flow applications. The presented simulation results, which include PID and fuzzy logic controllers, demonstrate that smooth control can be achieved by varying various parameters in combination. These findings offer valuable insights into the development of control strategies for low flow applications. © 2024 IEEE.

关键词： Three term control systems

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Closed-Loop System Identification of an Unstable Nonlinear System Using Koopman Operator 4

Closed-Loop System Identification of an Unstable Nonlinear S...

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4th International Symposium on instrumentation, control, Artificial Intelligence, and robotics, ICA-SYMP 2025

作者： Maneeloke, Benjaset Boonto, Sudchai Sanposh, Peerayot Tipsuwan, Yodyium Chinthaned, Natthawut Tanaprasitpattana, Warit Kasetsart University Dept. of Electrical Engineering Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. of Control Systems and Instrumentation Engineering Bangkok Thailand Kasetsart University Dept. of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331505400

This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlights the critical role of selecting appropriate observable functions to develop accurate and efficient Koopman models. We demonstrate that the resulting Koopman models exhibit excellent fitting and validation properties and retain the stabilizability of the original nonlinear systems. These models are verified through time and frequency responses under closed-loop control using a Linear Quadratic Regulator (LQR), confirming their effectiveness. Future work will extend this framework to more complex systems and incorporate machine learning techniques to refine the selection of observable functions. This approach aims further to enhance the adaptability and robustness of Koopman-based control strategies. © 2025 IEEE.

关键词： Dynamic mode decomposition

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230V-Multilevel DC-DC Converter for Low Input Voltage Range Using Adaptive Look-Up Table Tuned PI controller 3

230V-Multilevel DC-DC Converter for Low Input Voltage Range ...

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3rd International Conference on Power Systems and Electrical Technology, PSET 2024

作者： Samman, Faizal A. Maulana, Nassri Sadjad, Rhiza S. Universitas Hasanuddin Dept. of Electrical Engineering Makassar Indonesia PT. Poso Energy Divison of Instrumentation & Control Engineering Bogor Indonesia

ISBN: (纸本)9798350353204

This paper has presented a multilevel DC-DC boost converter for low input voltage ranges controlled using a proportional-integral (PI) controller, in which its proportional and integral parameter can be adaptively changed using look-up table technique to overcome the converter performance degradation due to load change. The circuit has been modeled, simulated, implemented and tested in real hardware. The comparative study between the simulation dan real hardware test results is analyzed and shows performance deviation due to a not-exact parametric similarity used in the simulation and hardware testing. Different loading conditions forces the converter responds the load with different performance. The adaptive look-up-table (LUT) PI controller has improved the output power capability and reduced the output voltage ripples of the converter compared to its counterpart conventional PI controller. Using the adaptive LUT PI controller, the boost converter can give output power around 4% higher than its counterpart the boost converter using conventional PI controller under the same load condition. The output voltages of adaptive LUT PI controller tends to be more stable under some load condition compared to the conventional PI controller. The adaptive controller can also slightly reduce the DC ripple voltage to be 0.120% out of 0.121% obtained using conventional PI controller. © 2024 IEEE.

关键词： Adaptive control systems

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Study Of Muscle Activation During The Articulation Of Phoneme Using Features Extracted From Electromyography Signals 20

Study Of Muscle Activation During The Articulation Of Phonem...

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20th IEEE India Council International Conference, INDICON 2023

作者： Nair, Remya Alfiya Parveen, P.C. Sabu, Justin Akshay, M. Sayana, M.V. Veena, K. Venugopal, G. Apj Abdul Kalam Technological University Nss College of Engineering Dept. of Instrumentation and Control Engineering Kerala Palakkad India

ISBN: (纸本)9798350305593

Humans express their emotions mostly through speech. People can speak effectively through the active coordination of facial as well as vocal muscles. The proposed study attempts to analyze the muscle activation during the articulation of phonemes, particularly '' (a) and '' (aa), which are commonly used in most Indian languages. In this work, the Malayalam language is selected for the study. Surface Electromyography signals are recorded from three facial muscles (Zygomaticus Major, Depressor Anguli Oris, and Mentalis) and one neck muscle (Anterior Belly of Digastric) of healthy female subjects using standard protocols. Root Mean Square (RMS) and mean frequency are extracted from the recorded signals. Further, classifiers namely Decision Tree, Random Forest, and KNN are applied to differentiate the phonemes '' (a) and '' (aa). The results show that the mean RMS of the signals from Mentalis is greater during the articulation of phonemes ' and '', compared to other muscles. In addition, KNN showed a maximum classification accuracy of 87 % while differentiating the phonemes with the extracted features. This study may be helpful for developing assistive devices for people suffering from speech disorders. © 2023 IEEE.

关键词： articulation facial and neck muscles Malayalam phoneme mean frequency root mean square surface electromyography

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