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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Kosiyanurak, Akkharachai Pothi, Nattachai Prasoetkarn, Natthawut Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand

ISBN: (纸本)9781643685403

This paper investigates the estimation of a straightforward mathematical model tailored for overseeing and regulating the motion of an AGV (Automated Guided Vehicle) equipped with differential drive systems. The mathematical model delineates the correlation between the input voltage signal of the DC motor and the resultant distance output, empirically tested within an open-loop system. This methodology facilitates the development of precise mathematical models aimed at mitigating errors in powertrains and mechanical motion components, including gears, chains, and ground-contacting tires, along with system friction. Moreover, a P controller system is devised to oversee the AGV motion. The stability and control efficacy are assessed through practical experimentation on the AGV's ability to attain predefined distances. Tests were conducted under two distinct conditions: case 1) AGV operation without any payload and case 2) AGV operation while bearing a 14 kg payload. The system's response to the input distance was meticulously observed. The average distance error is calculated at 1.74% of the designated control distance (2m, 3m, and 4m) across all cases. In the absence of a load (case 1), the average distance error remains consistent at 1.74% of the control distance, showcasing a motor speed response of 23.76 RPM (with a rise time of 2.1 s). Conversely, when subjected to a 14 kg payload (case 2), the average distance error marginally increases to 1.76% of the control distance, with a corresponding motor speed response of 23.71 RPM (and a rise time of 2.2 s). These results show the effectiveness of the control system, facilitated by the estimation of a simplistic mathematical model tailored specifically for AGV operations. Â© 2024 The Authors.

关键词： Closed loop systems

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Project Edubot: Exploring Pedagogical Approaches in High School Robotics Education 16

Project Edubot: Exploring Pedagogical Approaches in High Sch...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Nunes Daltro, Isabela Silva Santos, João Victor de Sousa, Guilherme Barbosa Martins, Rodrigo Pastrana, M.A. de Souza Baptista, Roberto Mechatronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil

ISBN: (纸本)9798350391084

This study focus on passive and active learning within the context of robotics education on public high schools. By synthesizing research findings and practical insights, this paper offers valuable recommendations for educators aiming to optimize the delivery of robotics education in public high schools, addressing the significance of the utilization of appropriate resources and technologies to support effective instruction. We implemented two distinct teaching methodologies to compare and study students’ reactions and learning outcomes: Group A experienced a passive methodology, while Group B engaged with an active methodology. We conducted a survey and the results show that the majority of the students prefer the active approach used in classes. ©2024 IEEE.

关键词： Contrastive Learning

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Hybrid Intelligent Sliding Mode Controller for Blood Glucose Regulation

Hybrid Intelligent Sliding Mode Controller for Blood Glucose...

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2024 Advances in Science and engineering Technology International Conferences, ASET 2024

作者： Nasar, Nabeel Jaradat, Mohammad A. Rhomdane, Lotfi Mechatronics Engineering Program American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350344134

Type 1 diabetic patients need insulin injections in order to maintain their blood glucose levels within safe limits as their bodies are not able to regulate it naturally. In this paper, the performance of a hybrid intelligent Sliding Mode Controller (SMC) based on Type-2 Fuzzy logic system (FSMC-T2) is studied for the regulation of the blood glucose level in a diabetic patient. In this controller the type-2 fuzzy logic system is utilized to tune the SMC parameters, furthermore, the Genetic Algorithm (GA) was used to tune the proposed controller for better performance. The glucose-insulin dynamic model is simulated for 24 hours with disturbances. The results of the GA-FSMC T2 are compared with FSMC Type 1 and Type 2 for comparison of results. The GA-FSMC T2 controller shows better performance in comparison to FSMC Type 1 and Type 2. The models are further tested by adding a disturbance in the form of an additional meal intake. All controllers regulate the blood glucose level to the set value even with disturbance added. The GA-FSMC T2 performed better than FSMC Type 1 and Type 2. © 2024 IEEE.

关键词： Glucose sensors

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Exploring Classification, Size, and Quality of Mangifera Indica L. Through Image Processing and AI Techniques 2

Exploring Classification, Size, and Quality of Mangifera Ind...

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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Wanthong, Irin Sri-On, Theeraphat Seangsri, Soontaree Khaengkarn, Sorada Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand Department of Mechatronics and Robotics Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-ok Chonburi Thailand

ISBN: (纸本)9781643685403

This paper introduces methods for efficiently classifying mangoes intended for export, a market valued at approximately 4,500 million baht annually. The classification process is divided into two primary components: size categorization and quality assessment. The first phase involves categorizing mango sizes into four distinct categories (M, 1L, 2L, 3L), while the second phase focuses on assessing mango quality, particularly detecting anthracnoseâ€"a prevalent disease affecting mangoes. This detection is achieved through image processing techniques, where images are converted into binary representations and analyzed using both Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs). Comparative analysis reveals that CNN outperforms ANN in size classification, achieving a remarkable train accuracy of 99.16% and a test accuracy of 88.0%. Furthermore, in quality classification, CNN demonstrates a train accuracy of 91.0% and a test accuracy of 88.0%. These findings underscore the effectiveness of CNN techniques in accurately classifying mangoes for export, thereby facilitating improved quality control and market competitiveness. Â© 2024 The Authors.

关键词： Convolutional neural networks

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Comparison of Bioinspired MLP Controllers for Mobile Robots Obstacle Following/Avoidance

Comparison of Bioinspired MLP Controllers for Mobile Robots ...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Luiz, Matheus De S. Pastrana, M.A. Da Silva, Lukas. A. Campagnucci, Pamela. R. A. N. Mendoza-Penaloza, Jose Benevides, Rafael R.L. Munoz, Daniel M. University of Brasilia Mechatronics Graduate Program Department of Mechanical Engineering Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN) based on the Multilayer Perceptron (MLP) have great potential to replace PID controllers due to their polynomial structure, allowing complex non-linear systems to be controlled. This article introduces the integration of four MLPs as alternatives to a traditional PID controller. These MLPs were trained through four bioinspired algorithms tailored for following tasks in mobile robots. The bioinspired algorithms employed for MLP network training include Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Month-Flame Optimization (MFO), and Artificial Hummingbird Algorithm (AHA). A comparative analysis was conducted between these MLPs and a classic PID controller, focusing on parameters such as overshoot (OS), settling time (ST), and steady-state error for different simulated scenarios. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Bringing Bearing Fault Detection to Embedded Systems Using Low-Cost Machine Learning Techniques

Bringing Bearing Fault Detection to Embedded Systems Using L...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Teixeira, Natalia S. Pastrana, M.A. Moura, Henrique G. Munoz, Daniel M. University of Brasilia Faculty of Gama Automotive Engineering Undergraduate Program Brasilia Brazil University of Brasilia Department of Mechanical Engineering Mechatronics Graduate Program Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Vibration analysis is crucial for predictive maintenance of bearing systems, aiming to reduce costs and prevent failures. This paper investigates signal processing techniques such as FFTs and Hilbert Transforms for fault diagnosis, alongside decision tree models, particularly the J48 algorithm within the WEKA environment, for fault classification. The study emphasizes the integration of signal processing and machine learning for effective fault diagnosis and maintenance. Notably, a classification model with low computational cost has been chosen, facilitating implementation in embedded systems. This model also offers interpretability of outputs, as it is based on decision trees of frequency components obtained through preprocessing. © 2024 IEEE.

关键词： Predictive maintenance

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Sub-optimal Perceptron Controller Using WOA Algorithm for Farming Watering Mobile Robot

Sub-optimal Perceptron Controller Using WOA Algorithm for Fa...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Pastrana, M.A. Oliveira, L.H. Bautista, J. Pinto-Lopera, Jesus Mendoza-Penaloza, Jose Munoz, Daniel M. University of the Amazonia Faculty of Engineering Systems Undergraduate Program Florencia Caquetá Colombia University of Brasilia Mechatronics Graduate Program Department of Mechanical Engineering Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Artificial neural networks (ANNs) are intricate mathematical models, drawing inspiration from the biological nervous system, and offering intelligence alongside nonparametric capabilities. The efficacy of ANNs heavily relies on their learning process. Heuristic search algorithms have been proposed in literature as reliable options for optimizing neural networks utilizing the Perceptron architecture. This paper presents an suboptimal neural network Perceptron training method employing the Whale Optimization Algorithm for the application of farming watering mobile robots. To achieve this, a fitness function based on system responses such as overshoot, settling Time, and steady-state Error was developed. The sub-optimal Perceptron controller was then implemented using MATLAB, CoppeliaSim software and the EVA robot, resulting in a 66.17% overshoot, a 4.7% steady-state error, and a settling time of 3.05 seconds. Moreover, the sub-optimal Perceptron controller was mapped onto a System on Chip FPGA AMD-Xilinx Zynq 7020, resulting in a hardware resources consumption of 1,870 (3.52%) Lookup table, 2 (0.9%) Digital Signal Processing blocks, 1,019 (0.96%) Flip-Flops and a power consumtion of 0.005 W. Finally, Hardware-in-The-Loop validation was performed using CoppeliaSim, Python, Universal Direct Memory Access, and the EVA robot. The results showed an overshoot of 94.83%, a settling time of 2 seconds, and a steady-state error of 4.5%. © 2024 IEEE.

关键词： MATLAB

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Efficiency improvement of automated production line by conversion of subroutine configuration

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International Journal of Advanced Manufacturing Technology 2023年第7-8期129卷 3537-3547页

作者： Chen, Po-Tuan Cheng, Yu-Lin Department of Vehicle Engineering National Taipei University of Technology Taipei Taiwan Technical and Vocational Program in Mechatronics National Taipei University of Technology Taipei Taiwan

programmable control for automated production is an essential technology for industrial development. In addition, a flexible main control system and scheduling management can significantly improve production efficiency. This study improved a programmable logic controller (PLC) subroutine module and communication methods using the modular production system (MPS) automated workstation developed by Festo to optimize the process of production. First, a simulated production line with feeding, transportation, discrimination, and processing stations was set up in a laboratory. Experiments and tests were performed, and data were collected. Consequently, different program editing and planning methods, such as program modularization, step system, and subroutines of the busbar, were proposed for PLC and automation systems. The design with clearer and more modularized subroutines was used to improve the production line performance and stability and achieve dynamic scheduling to optimize the production line efficiency to meet the demands. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： programmable logic controllers

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Exploring Techniques for Estimating Distance in Leader-Follower AGV Systems 2

Exploring Techniques for Estimating Distance in Leader-Follo...

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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Muenngam, Chetsadakorn Khaewnak, Nopparut Srisertpol, Jiraphon Prasoetkarn, Natthawut Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology 111 University avenue Muang district Nakhon Ratchasima30000 Thailand

ISBN: (纸本)9781643685403

The application of Automated Guided Vehicles (AGVs) for workpiece transportation in production processes is commonplace, particularly in the context of Industry 4.0. However, the high cost associated with AGVs presents a significant challenge. This paper proposes an approach to AGV tracking using a combination of camera-based QR code detection and ultrasonic sensors. The objective is to regulate the distance between leading and following AGVs, thereby addressing the operational costs associated with expensive equipment. Experimental investigations were conducted to assess the performance of QR symbols and color bars under varying lighting conditions, ranging from 200 lux to 650 lux. Accurate distance measurements were achieved within a range of 150 cm. In lower lighting conditions (100 lux to 250 lux), the RGB color bar detection failed at distances below 40 cm, whereas QR Code detection remained robust. Angle measurements demonstrated accurate readings up to 30 degrees from the camera's center, within distances of 50 to 125 cm, with an anticipated deviation of no more than 0.5 degrees. Subsequently, QR code symbols were chosen as the experimental control symbol, complemented by ultrasonic sensors for inter-vehicle distance maintenance. During practical testing, if the measured distance falls below 60 cm. while moving in a straight line, the motor ceases operation. Conversely, if the distance exceeds 80 cm, the motor activates, allowing the follower AGV to uphold the specified distance behind the leader AGV. Â© 2024 The Authors.

关键词： Ultrasonic sensors

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Design and Construction of a Low-Cost Combat Robot 16

Design and Construction of a Low-Cost Combat Robot

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Costa, R.B. Itacaramby, G. Cabral, J. Pastrana, M.A. Peñaloza, J.M. Muñoz, Daniel M. Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Aerospace Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Software Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil

ISBN: (纸本)9798350391084

This paper presents the design and construction of a low-cost combat robot named Artemis, developed for participation in the Robocore Experience 2024 competition. The project emphasizes the integration of cost-effective components and innovative methodologies to create a competitive robot. The ESP32 microcontroller was selected for its advantages in energy efficiency and connectivity, surpassing traditional platforms like Arduino. The construction process involved several phases, including planning, development, testing, correction, and performance evaluation, utilizing tools such as CAD software for design and 3D printing for fabrication. Key components included a DC motor, L298N H-bridge, and a LiPo battery, all chosen to optimize performance while adhering to budget constraints. The robot’s design evolved through iterative testing and adjustments, ultimately leading to a successful competition debut. This work highlights the importance of resourcefulness and collaboration in robotics, showcasing how educational institutions can foster innovation in engineering projects. ©2024 IEEE.

关键词： Budget control

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