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9 pages, 1763 KiB

Open AccessProceeding Paper

Robust and Reliable State Estimation for a Five-Axis Robot Using Adaptive Unscented Kalman Filtering

by Geetha Sundaram, Selvam Bose, Vetrivel Kumar Kandasamy and Bothiraj Thandiyappan

Eng. Proc. 2025, 95(1), 1; https://doi.org/10.3390/engproc2025095001 - 26 May 2025

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Robust robot manipulation hinges on effective state estimation. The VRT 6 robot leverages an inertia measurement unit with triaxial gyroscopes, magnetometers, and accelerometers, as well as a position sensor, but these sensors are plagued by noise that demands rigorous filtering. To tackle this, [...] Read more.

Robust robot manipulation hinges on effective state estimation. The VRT 6 robot leverages an inertia measurement unit with triaxial gyroscopes, magnetometers, and accelerometers, as well as a position sensor, but these sensors are plagued by noise that demands rigorous filtering. To tackle this, an adaptively scaled unscented Kalman filter was employed. The filter’s scaling parameter was meticulously optimized using density- and moment-based techniques, as both system properties and estimated state impact this crucial parameter. A Maximum Likelihood Estimation (ML) substantiates the enhanced quality of the estimated velocity and acceleration, on par with the position estimate. Minimizing measurement prediction error (MMPE) also shows better results with less RMSE when compared to fixed-kappa values, and the quality of position estimates is higher with the increase in the domain of the scaling parameter. By carefully selecting the adaptive scaling parameters’ range to minimize sigma point weights and ensure the positive definiteness of the covariance matrix, this enhanced UKF method achieved markedly superior state estimates compared to standard UKF implementations. Full article

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10 pages, 2198 KiB

Open AccessProceeding Paper

Tuning and Performance Analysis of Second-Order Linear Active Disturbance Rejection Controller for Trajectory Tracking and Balancing the Rotary Inverted Pendulum

by Janeshwaran Gunasekaran and Ezhilarasi Deenadayalan

Eng. Proc. 2025, 95(1), 2; https://doi.org/10.3390/engproc2025095002 - 27 May 2025

Viewed by 166

Abstract

Second-order Linear Active Disturbance Rejection Controller (SLADRC) is a powerful control technique. Ongoing research is focused on simplifying tuning procedures, extending applicability to handle more complex systems, and ensuring efficient real-time implementation. In this proposed work, four different tuning approaches, using the Atomic [...] Read more.

Second-order Linear Active Disturbance Rejection Controller (SLADRC) is a powerful control technique. Ongoing research is focused on simplifying tuning procedures, extending applicability to handle more complex systems, and ensuring efficient real-time implementation. In this proposed work, four different tuning approaches, using the Atomic Orbital Search (AOS) optimization algorithm concerning the number of tuning parameters, are presented. The performance of each tuning method for stabilizing the rotary inverted pendulum in the upright position and tracking trajectory is analyzed and validated through simulation and experimentation. The results indicate that the reduced number of SLADRC controller parameters tuned using AOS optimization provides superior performance compared to the controller with more tuning parameters for the nonlinear rotary inverted pendulum. From the analysis method, II tuning,

b_{0}, ω_{c}, a n d k

provide the optimum results of settling time (

T_{s}

), 1.5 s, and maximum angle deviation of

θ (3.8 °), α (3 °)

. Full article

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13 pages, 2916 KiB

Open AccessProceeding Paper

Biogas Production Using Flexible Biodigester to Foster Sustainable Livelihood Improvement in Rural Households

by Charles David, Venkata Krishna Kishore Kolli and Karpagaraj Anbalagan

Eng. Proc. 2025, 95(1), 3; https://doi.org/10.3390/engproc2025095003 - 28 May 2025

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Abstract

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied [...] Read more.

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

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9 pages, 1736 KiB

Open AccessProceeding Paper

Efficiency Enhancement and Estimation of Photovoltaic Energy Generation Using Dual-Axis Tracking Systems

by Aditya Aggarwal, Himanshu Himanshu, Manav Sidana, Girish Gupta, Ishtdeep Singh Sodhi and Anamika Sharma

Eng. Proc. 2025, 95(1), 4; https://doi.org/10.3390/engproc2025095004 - 29 May 2025

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Abstract

The global need to transition towards sustainable energy sources has increased the exploration of efficient methods to harness solar energy. Traditional solar panels, being stationary, often fail to capture the rays of the sun optimally across the day. This paper presents a SunPath [...] Read more.

The global need to transition towards sustainable energy sources has increased the exploration of efficient methods to harness solar energy. Traditional solar panels, being stationary, often fail to capture the rays of the sun optimally across the day. This paper presents a SunPath navigator system that dynamically adjusts the solar panel’s angle, ensuring maximum exposure to the sun. The developed SunPath navigator system achieves a 27.67% average energy gain. This work has utilised the applications of various machine learning models, such as decision trees, AdaBoost, and K-nearest neighbour, for predicting energy generation. The relevance of these models is analysed based on multiple types of error such as MAE, MSE, RMSE, and R². The decision tree outperforms the other two models with a minimum error rate. It is paving the way for a future where solar energy is a primary, economical, and user-friendly power source in urban and rural areas. The dual-axis tracking system not only enhances energy generation but also estimates future energy generation. Full article

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8 pages, 4565 KiB

Open AccessProceeding Paper

Vision Sensing Techniques for TIG Weld Bead Geometry Analysis: A Short Review

by Panneer Selvam Periyasamy, Prabhakaran Sivalingam, Vishwa Priya Vellingiri, Sundaram Maruthachalam and Vinod Balakrishnapillai

Eng. Proc. 2025, 95(1), 5; https://doi.org/10.3390/engproc2025095005 - 30 May 2025

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Abstract

Automated and robotic welding have become standard practices in manufacturing, requiring precise control to maintain weld quality without relying on skilled welders. In Tungsten Inert Gas (TIG) welding, monitoring the weld pool is crucial for ensuring the necessary weld penetration, which is vital [...] Read more.

Automated and robotic welding have become standard practices in manufacturing, requiring precise control to maintain weld quality without relying on skilled welders. In Tungsten Inert Gas (TIG) welding, monitoring the weld pool is crucial for ensuring the necessary weld penetration, which is vital for maintaining weld integrity. Real-time observation is essential to prevent defects and improve weld quality. Various sensing technologies have been developed to address this need, with vision-based systems showing particular effectiveness in enhancing welding quality and productivity within the framework of Industry 4.0. This review looks at the latest technologies for monitoring weld pools and bead shapes. It covers methods like using Complementary Metal-Oxide Semiconductors (CMOS) to take clear images of the melt pool for better process identification, Active Appearance Model (AAM) to capture 3D images of the weld pool for accurate penetration measurement, and Charge-Coupled Devices (CCD) and Laser-Induced Breakdown Spectroscopy (LIBS) to analyze plasma spectra and create material composition graphs. Full article

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7 pages, 2077 KiB

Open AccessProceeding Paper

Flatfoot Detection in an Indian Population: Validation of Morphological Indices Using a Diagnostic Device

by Ketan Kalghatgi, Khyati Verma and Bishwaranjan Das

Eng. Proc. 2025, 95(1), 6; https://doi.org/10.3390/engproc2025095006 - 3 Jun 2025

Viewed by 220

Abstract

Flatfoot, or pes planus, is a condition where the foot’s arch collapses, leading to complications such as pain, gait abnormalities, and an increased risk of injury. Accurate and early diagnosis is critical for effective treatment. Traditional diagnostic methods, including radiographic imaging, footprint analysis, [...] Read more.

Flatfoot, or pes planus, is a condition where the foot’s arch collapses, leading to complications such as pain, gait abnormalities, and an increased risk of injury. Accurate and early diagnosis is critical for effective treatment. Traditional diagnostic methods, including radiographic imaging, footprint analysis, and plantar pressure measurement, often require specialized equipment and are subjective. This study proposes a novel diagnostic device that captures 2D plantar foot images to calculate key morphological indices, including the Staheli Index, Clark’s Angle, and Chippaux–Smirak Index, for flatfoot detection. The device, designed with off-the-shelf components, includes a transparent toughened glass platform and LED illumination to capture images using web cameras. A Python-based application was developed for image acquisition, segmentation, and stitching. The device was tested on 55 participants aged 18–28, and the extracted morphological indices were validated against established thresholds for flatfoot diagnosis. The results showed that the Staheli Index, Chippaux–Smirak Index, and Clark’s Angle reliably detected flatfoot in participants. The study highlights the potential of this device for non-invasive, accurate, and rapid flatfoot diagnosis. Future advancements in deep learning could enhance its capabilities, making it a valuable tool for proactive healthcare in foot deformity detection. Full article

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12 pages, 281 KiB

Open AccessProceeding Paper

Linguistic Intuitionistic Fuzzy VIKOR Method with the Application of Artificial Neural Network

by John Robinson Peter Dawson and Leonishiya Arockia Selvaraj

Eng. Proc. 2025, 95(1), 7; https://doi.org/10.3390/engproc2025095007 - 3 Jun 2025

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Abstract

This paper proposes Linguistic Intuitionistic Fuzzy (LIF) aggregation operators, LIF-energies, LIF-correlation, and LIF-correlation coefficients. Supporting theorems are also proven for the proposed functions, which are utilized in the Linguistic Intuitionistic Fuzzy–Vlse Kriterijumska Optimizacija Kompromisno Resenje (LIF-VIKOR) method within Decision Support Systems (DSS). Additionally, [...] Read more.

This paper proposes Linguistic Intuitionistic Fuzzy (LIF) aggregation operators, LIF-energies, LIF-correlation, and LIF-correlation coefficients. Supporting theorems are also proven for the proposed functions, which are utilized in the Linguistic Intuitionistic Fuzzy–Vlse Kriterijumska Optimizacija Kompromisno Resenje (LIF-VIKOR) method within Decision Support Systems (DSS). Additionally, numerical examples are presented to validate the method. The sensitivity analysis of weighting vectors is conducted, and the consistency of final rankings affirms the robustness of the proposed approaches. Arithmetic operations, specifically subtraction and division, are applied to LIF numbers (LIFNs) within the LIF-VIKOR algorithm. Furthermore, a function called the Linguistic Median Membership (LMM) function is introduced to convert LIFN values into crisp numbers. In the LIF-VIKOR algorithm, the proposed correlation coefficient is used for ranking alternatives, while the entropy method is applied to compute weights. Sensitivity analysis is performed to ensure the consistency of the proposed method. Finally, an Artificial Neural Network (ANN) is integrated into the VIKOR algorithm to enhance computational efficiency, reducing the time and manpower required to solve the model. Full article

8 pages, 1856 KiB

Open AccessProceeding Paper

COP Enhancement of Peltier-Based Dehumidifiers

by Srithar Karuppiah, Venkatesan Raman, Rajkumar Natarajan and Saravanan Rajagopal

Eng. Proc. 2025, 95(1), 8; https://doi.org/10.3390/engproc2025095008 - 4 Jun 2025

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Abstract

A vital procedure for eliminating moisture from the air, dehumidification is necessary for processes like desalination and air conditioning. The Peltier dehumidifier, sometimes referred to as a thermoelectric dehumidifier, removes moisture using the Peltier effect to generate a temperature differential across a Peltier [...] Read more.

A vital procedure for eliminating moisture from the air, dehumidification is necessary for processes like desalination and air conditioning. The Peltier dehumidifier, sometimes referred to as a thermoelectric dehumidifier, removes moisture using the Peltier effect to generate a temperature differential across a Peltier module. Nevertheless, inadequate heat removal from the hot side of the module and a low coefficient of performance (COP) are common problems with Peltier-based dehumidifiers. By combining baffles or turbulators with Peltier plates to increase heat transfer rates, this study overcomes these drawbacks and raises the dehumidifier’s COP and thermal enhancement factor (TEF). On the hot side of the Peltier module, airfoil-shaped baffles are used in the experimental setup to enhance heat dissipation and speed up turbulence. Performance significantly improved, as evidenced by the findings, with the TEF rising to 3.2. Furthermore, the COP improved from 0.06 to 0.45, and the water condensation rate rose to a high of 35 mL per hour. These improvements are ascribed to the higher heat transfer rates made possible by the baffles, which enable the more effective cooling of the Peltier module’s cold side. This study demonstrates how turbulators can increase Peltier-based dehumidifiers’ effectiveness and make them more practical for industrial settings, especially in areas with limited water supplies. According to the results, thermoelectric dehumidification systems can function much better overall if heat transmission on the Peltier module’s hot side is optimized. Full article

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9 pages, 542 KiB

Open AccessProceeding Paper

Hamming Distance-Based Intuitionistic Fuzzy Artificial Neural Network with Novel Back Propagation Method

by John Robinson Peter Dawson and Wilson Arul Prakash Selvaraj

Eng. Proc. 2025, 95(1), 9; https://doi.org/10.3390/engproc2025095009 - 6 Jun 2025

Viewed by 44

Abstract

An artificial neural network (ANN)-based decision support system model, which aggregates intuitionistic fuzzy matrix data using a recently introduced operator, is developed in this work. Several desirable features related to distance measures of aggregation operators and artificial neural networks, including the backpropagation method, [...] Read more.

An artificial neural network (ANN)-based decision support system model, which aggregates intuitionistic fuzzy matrix data using a recently introduced operator, is developed in this work. Several desirable features related to distance measures of aggregation operators and artificial neural networks, including the backpropagation method, are investigated to support the application of the proposed methodologies to multiple attribute group decision-making (MAGDM) problems using intuitionistic fuzzy information. A novel and enhanced aggregation operator—the Hamming–Intuitionistic Fuzzy Power Generalized Weighted Averaging (H-IFPGWA) operator—is proposed for weight determination in MAGDM situations. Numerical examples are provided, and various ranking techniques are used to demonstrate the effectiveness of the suggested strategy. Subsequently, an identical numerical example is solved without bias using the ANN backpropagation approach. Additionally, a novel algorithm is created to address MAGDM problems using the proposed backpropagation model in an unbiased manner. Several defuzzification operators are applied to solve the numerical problems, and the efficacy of the solutions is compared. For MAGDM situations, the novel approach works better than the previous ANN approaches. Full article

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9 pages, 1466 KiB

Open AccessProceeding Paper

Assessment of Lithium Ferrous Phosphate Battery Cells Under Series Balancing Mode—Performance and Health Behaviours

by Niveditha Balagopal Menon, Samridhi Mehta, Pranavya Punnakkattuparambil, Preetha Punnakkattuparambil, Vidhya Marimuthu, Nanthagopal Kasianantham, Tabbi Wilberforce and Jambulingam Ranjitha

Eng. Proc. 2025, 95(1), 10; https://doi.org/10.3390/engproc2025095010 - 6 Jun 2025

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Abstract

Electric vehicles have recently gained greater attention across all countries for transportation purposes in on-road and off-road forms due to their supreme performance and clean eco-friendliness status. Lithium-ferrous phosphate batteries are the primary energy storage devices in electric vehicles due to their higher [...] Read more.

Electric vehicles have recently gained greater attention across all countries for transportation purposes in on-road and off-road forms due to their supreme performance and clean eco-friendliness status. Lithium-ferrous phosphate batteries are the primary energy storage devices in electric vehicles due to their higher energy density, longer lifespan, and lower self-discharge rate. They also possess several technical advantages, including a wider range of applications, economic affordability, an environmentally friendly nature, and, most importantly, superior electrochemical performance, which makes them a strong competitor to lead acid batteries. In the present study, a performance and health assessment of a lithium ferrous phosphate battery (LFP) pack consisting of 23 cells connected in series balancing mode with a 7360 Wh maximum energy storage capacity has been carried out at various current ranges of operation such as 3 A, 5 A, and 8 A in a typically developed battery management system to estimate their optimized performance and overall health conditions. Further study has been conducted to investigate the characteristics of LFP packs under various power-mode conditions, ranging from 20 W to 750 W. This experimental study revealed that the LFP battery pack exhibits a remarkable state-of-charge capability, achieving 58% charging in a 3.3-h runtime period. A similar decreasing trend was also observed during power-mode operations. Furthermore, the LFP battery pack was fully charged after achieving a 50% State of Charge (SOC) under every current-mode condition, providing reliable outputs under the loading conditions. It is also stated that the state of health of the lithium ferrous phosphate is significantly higher at 92% during the entire investigation, which reflects the good thermal stability of the LFP battery pack for temperature variations from 26 °C to 31 °C. Finally, it is concluded that the LFP could be one of the most favourable energy storage systems due to its longer lifespan and its great affordability in automotive applications. Full article

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11 pages, 1119 KiB

Open AccessProceeding Paper

Automatic Ladle Tracking with Object Detection and OCR in Steel Melting Shops

by Kabil Murugan, Mahinas Senthilmurugan, Venbha V. Senthilkumar, Harshita Velusamy, Karthiga Sekar, Vasanthan Buvanesan and Manikandan Venugopal

Eng. Proc. 2025, 95(1), 11; https://doi.org/10.3390/engproc2025095011 - 12 Jun 2025

Viewed by 56

Abstract

A ladle tracking system in steel production plants is essential for optimizing the ladle transportation between different processing units. The currently used technologies for ladle tracking, including Radio Frequency Identification (RFID) systems, are not effective due to their high maintenance costs and poor [...] Read more.

A ladle tracking system in steel production plants is essential for optimizing the ladle transportation between different processing units. The currently used technologies for ladle tracking, including Radio Frequency Identification (RFID) systems, are not effective due to their high maintenance costs and poor performance in harsh conditions, leaving a significant gap in developing an automated ladle tracking system. This paper proposes two innovative solutions to address these problems: a computer-vision-based ladle tracking system and an integrated approach of preprocessing techniques with optical character recognition (OCR) algorithms. The first method utilizes a YOLOv8 framework for detecting the two classes from the input images, such as the ladles and their unique numbers. This method achieved a precision of 0.983 and a recall of 0.998 in detecting the classes. The second method involves several preprocessing steps prior to the application of OCR. This is suitable for challenging environments, where the clarity of the images may be compromised. EasyOCR with enhanced preprocessing was able to extract the ladle number with a confidence score of 0.9948. The results demonstrate that vision-based automated ladle tracking is feasible in steel plants, improving operational efficiency, ensuring safety, and minimizing human intervention. Full article

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8 pages, 1981 KiB

Open AccessProceeding Paper

Breakdown Characteristics of Unequal Sphere–Sphere Electrode Configuration Under DC Stress

by Indhulekha Jayachandran and Gowrishankar Shanmugam

Eng. Proc. 2025, 95(1), 12; https://doi.org/10.3390/engproc2025095012 - 13 Jun 2025

Abstract

Failure of air gap insulation is one of the prominent issues in insulation coordination for outdoor applications. Though uniform electric field distribution is desirable, the difficulty in achieving it often makes insulation engineers settle for weakly non-uniform fields. One of the electrode systems [...] Read more.

Failure of air gap insulation is one of the prominent issues in insulation coordination for outdoor applications. Though uniform electric field distribution is desirable, the difficulty in achieving it often makes insulation engineers settle for weakly non-uniform fields. One of the electrode systems known for its weakly non-uniform field is sphere gap, which is reliable due to its standardized breakdown characteristics. Though the breakdown characteristics of spheres with the same diameter are widely studied and standardized, spheres with unequal diameters have received minimal attention. In this paper, an attempt is made to study the breakdown characteristics of unequal spheres under DC stress in atmospheric air. The experimental breakdown studies were conducted for different spacings of spheres with unequal diameters of 100 mm, 50 mm, and 20 mm. The electric field variation for the experimental combination of sphere gaps and their corresponding utilization factors were computed using ANSYS 2024 R1. The results obtained were compared with the standard sphere gap. An unequal sphere gap has a non-uniform electric field distribution and a lower utilization factor compared to the standard sphere gap. It appears that the larger sphere experiences the maximum electric field, regardless of whether it is high-voltage or ground electrode. However, its breakdown characteristics are found to be comparable with standard sphere gap up to certain gap spacing under DC voltage. Full article

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