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2022 International Conference on Electronic systems and Intelligent Computing, ICESIC 2022

作者： Valluru, Sudarshan K. Thareia, Hitesh Center for Control of Dynamical Systems and Computation Dept. of Electrical Engineering Delhi Technological University Delhi110042 India

ISBN: (纸本)9781665483858

This paper emphasizes maneuvering control of Autonomous Underwater Vehicle (AUV) with the help of Linear-Proportional Integral Derivative (L-PID) and Fractional Order PID (FOPID) controllers. The values of the gain parameters of L-PID (Kp, Ki, Kd) and FOPID (Kp, Ki, Kd,λ, μ) are tuned by Simulated Annealing (SA) and Moth Flame optimization (MFO) techniques. The performance of both the controllers is compared and the better algorithm to tune the parameters of the controllers is determined. A step function is applied to the system's input to test the AUV, and the corresponding response to the input function is examined. The transient parameters of the AUV, such as rise time, settling time, overshoot, and performance index IT AE were calculated and compared. The investigatory results show that both the algorithms used to tune the FO PID controller accurately steer the AUV. Also, the MFO tuned FOPID controller is more efficient than the SA tuned FOPID controller. © 2022 IEEE.

关键词： Simulated annealing

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Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry

Monitoring and Forecasting Quality Indicators of Predough Pr...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Andrii Zhyltsov dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of electromagnetic systems The Institute of Electrodynamics of the National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them.

关键词： Force Process control Production Machine learning Quality control Humidity Predictive models Stability analysis Monitoring Thermal stability

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Multi-Aspect Optimal Sliding Mode controller for a Mecanum Wheeled Robot 11

Multi-Aspect Optimal Sliding Mode Controller for a Mecanum W...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Allahyari, Sohrab Rahmanei, Hamid Moosavian, S. Ali A. K. N. Toosi University of Technology Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems Laboratory Dept. of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

Four-wheel drive Mecanum robots have gained attention due to their ability to move in all directions, which allows them to work in tight and complex environments. For this reason, ensuring precise control of these robots along predefined trajectories is crucial. This work presents a comparative study on the effects of parametric uncertainties, external disturbances, measurement noises, and initial deviations on the trajectory-Tracking performance of a 4-wheel drive Mecanum robot. First, the kinematic and kinetic models of the Mecanum robot are introduced. Then, the integral sliding mode control is designed, and proof of stability is provided. In addition, we explore other control strategies, including PID, feedback linearization, sliding mode, and adaptive sliding mode control, that are designed for this robot. Furthermore, the particle swarm optimization algorithm is hired for the controllers with a cost function as the total sum of average error, maximum error, and final error. Optimization has been done on all controllers to compare the results fairly. To appraise the effectiveness of the proposed control optimization methods, simulations are carried out in MATLAB/Simulink. The results reveal that the proposed ISMC method performs best in both defined scenarios compared to other controllers. However, it must be noted that the ISMC controller exhibits limitations when facing significant uncertainties in the dynamic model. This study underscores the effectiveness of our proposed control method and provides valuable insights into the practical implementation controller for the Mecanum robot in real-world applications. © 2023 IEEE.

关键词： Three term control systems

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Calculation of Magnetoelectric Brushless DC Electric Motor in Polar Coordinates

Calculation of Magnetoelectric Brushless DC Electric Motor i...

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： Alexsandr A. Afanasyev Valery S. Genin Lidia N. Vasileva Nadezhda N. Ivanova dept. of Automation and Control in Technical Systems Ulianov Chuvash State University Cheboksary Russia dept. of Mathematical and Hardware Support of Information Systems Ulianov Chuvash State University Cheboksary Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

The electromagnetic calculation of magnetoelectric switched-type motors with high-energy permanent magnets by the method of separating Fourier variables in polar coordinates is considered. A two-dimensional analytical model is used taking into account the real geometry of permanent magnets, stator slots with a fixed finite magnetic permeability of the teeth and the yoke of the stator and rotor cores. To do this, the single magnetic field of the machine is divided into a set of cylindrical strips, analyzed independently of each other. At the boundaries of the strips, the conditions for conjugating magnetic fields are met: scalar magnetic potentials and normal components of magnetic induction do not undergo jumps. Magnetic potentials are determined from the solution of the Dirichlet boundary value problem, and induction, which is usually determined from the solution of the Neumann boundary value problem, is here determined by differentiating the expression for the magnetic potentials.. The latter eliminates the need to solve additionally the Neumann boundary value problem. In this case, an original technology for finding Fourier constants is used, based on the equality of magnetic potentials and magnetic inductions at the boundaries of the strips. Graphs of magnetic induction in the air gap at the pole division are presented, obtained taking into account the stator gearing, winding harmonics of the magnetomotive force and the geometric structure of the arrangement of permanent magnets. It has been shown that bevel of the stator slots by a tooth pitch makes it possible to eliminate the reactive torque of the motor.

关键词： Stator cores Strips Boundary value problems Magnetic separation Magnetic cores Windings Magnetoelectric effects

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Training Swinging Door Trending Compression Algorithm for IoT devices

Training Swinging Door Trending Compression Algorithm for Io...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Juan David Arias Correa Alex Sandro Roschildt Pinto Carlos Montez Post-graduate Program of Automation Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms.

关键词： Training Performance evaluation Communication systems Data compression Prediction algorithms Market research Internet of Things Computational complexity Compression algorithms

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SWOT analysis in building a blockchain data sharing system

SWOT analysis in building a blockchain data sharing system

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Energy Efficiency and Agricultural engineering (EE&AE), International Conference on

作者： Teodora Hristova Peyo Hristov Grigor Mihaylov Albena Taneva dept. Electricity and automation University of Mining and Geology “St.Ivan Rilski” Sofia Bulgaria dept. Software engineering Cisco Systems Sofia Bulgaria Dept. of Telecommunications University of Telecomunication and Post Sofia Bulgaria dept. Control Systems Technical University of Sofia Branch Plovdiv Bulgaria

ISBN: (数字)9798350369380

ISBN: (纸本)9798350369397

The article analyzes the four main types of blockchains. These are open (public), closed (private), hybrid, and consortium. The latter two simultaneously and to varying degrees have characteristics of both open and closed. Their advantages and disadvantages are defined. However, the variety of platforms that cannot be accurately classified as a specific type of network makes it difficult for users to choose the appropriate one when sharing a given data stream. Therefore, a SWOT analysis of the two main types of chains - closed and open - was made to determine their advantages, disadvantages, threats, and opportunities. It was found that the main difficulty in choosing a type of blockchain is the constantly changing legislative framework. Furthermore, an appropriate platform can be selected according to the specifics of the material flow, privacy, security, quantity, speed, and others of data transmission.

关键词： Data privacy Costs Law Data security Buildings Process control Organizations

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EXAMINATION OF WATERPROOF POCKETS AS PROTECTIVE CARRIERS FOR SMART GARMENTS

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Tekstil ve Muhendis 2022年第126期29卷 80-87页

作者： Akkan, Taner Kara, Şükran Ağin, Berk Yeşİlpinar, Sevil Şenol, Yavuz Dokuz Eylul University Izmir Vocational School Department of Mechatronics Izmir Turkey Dokuz Eylul University Faculty of Engineering Department of Textile Eng. Izmir Turkey İstanbul Technical University Control & Automation Engineering Dept. İstanbul Turkey Dokuz Eylul University Faculty of Engineering Electrical and Electronics Eng. Dept. Izmir Turkey

The importance of smart garments is increasing day by day for entertainment, sports, medical and military fields. Both hard electronics and textile based soft electronics find application in these areas. In our previous study, we focused on crew loss detection system that was applicable for team sports such as sailing. We designed a two pieces electronic system in which a master system was fixed on the boat and a slave system was implemented in the sailing garments. This study brought a new requirement;the need of a waterproof case that would protect the electronic slave system from sea water in case the sailors fall overboard. As a result of this need, in this study, we have designed and tested waterproof pockets that could serve as waterproof carriers for the slave system of sailing garments. For this purpose, studies were carried out using two different approaches. In the first approach, 15 types of pockets were developed by using three different fabric materials and 5 different seam sealing techniques. These pocket prototypes were tested by exposing them to the water for 12 h. In the second approach, an electronic circuit was developed by using a humidity sensor to test the pocket samples those were immersed to water. According to the results of the first approach, samples containing polyester base fabric, polyurethane and polyester membrane and double-sided sealing tape gave the best results. By converting the best pocket design into a garment sleeve, the humidity sensor containing test apparatus was tested and measurements were taken successfully from the system © 2022. Tekstil ve *** Rights Reserved

关键词： Humidity sensors

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Magnetomotive Force and Winding Coefficients of Alternating Current Windings

Magnetomotive Force and Winding Coefficients of Alternating ...

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International Ural Conference on Measurements (UralCon)

作者： Alexsandr A. Afanasyev Nadezhda N. Ivanova Lidia N. Vasileva dept. of Automation and Control in Technical Systems Ulianov Chuvash State University Cheboksary Russia dept. of Mathematical and Hardware Support of Information Systems Ulianov Chuvash State University Cheboksary Russia

ISBN: (数字)9798350386028

ISBN: (纸本)9798350386035

The physical nature of the magnetomotive force (MMF) of an alternating current winding, discretely located in slots and being a source of a magnetic field that has both potential and vortex components, the latter being limited in the space of the slot, is considered. It is shown that in this capacity the role of the MDS is played by a set of magnetic sheets of slot currents, which, in terms of location and duration of sections with linear and nonlinear changes, can differ significantly from the generally accepted (classical) MDS winding. An analytical description of the stepped classical MMF curve of a winding with an integer and a fraction is proposed in the form of a set of expansions into a trigonometric series of MMF curves of coils, presented in the form of two-pole rectangles, having different heights and bases with a shortened winding pitch. It is shown that the frequency response of a fractional winding can be used to find the spectrum of its distribution coefficients for a known arrangement of coils in the slots. It was found using the example of a fairly simple fractional winding with a fractional denominator equal to 2 that, firstly, determining the spectrum of distribution coefficients using a well-known formula for windings with an integer by replacing this number with some equivalent one can lead to significant errors; secondly, variation in the winding pitch significantly changes the amplitudes of the higher harmonics of the MMF, including the appearance of harmonics with an order that is a multiple of three.

关键词： Coils Power engineering Electric potential Windings Force Harmonic analysis Frequency response Magnetic analysis Magnetic fields Physics

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Proposal for a Job Management Tool for Deep Learning in a Mixed Environment of Heterogeneous GPUs

Proposal for a Job Management Tool for Deep Learning in a Mi...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Nobuyuki Ishii Aoi Kondo Hiroaki Koga Dept. Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

In recent years, the use of GPUs for computation has become commonplace in deep learning. It is not uncommon for deep learning labs to procure GPU servers for computation without standardising specifications such as GPU architecture and VRAM capacity, resulting in a heterogeneous GPU server environment. Container technology is also widely used as a method of isolating software execution environments. Among them, Docker is the de facto standard for container platforms. In this paper, we have developed a management system that can allocate deep learning training jobs to GPU servers (workers) using container technology to absorb differences in execution environments in heterogeneous GPU server environments. In experiments, we confirmed that the proposed system can estimate the completion time of training for each worker and can detect Out-Of-Memory (OOM) of GPUs in advance. We were able to confirm in advance the “inference time” and the “possibility of OOM”, which are difficult to predict when performing deep learning. We have succeeded in obtaining the “predicted value of learning time” and “possibility of OOM” that engineers need to know in advance, and have shown that the proposed system is effective in deep learning tests.

关键词： Deep learning Training Graphics processing units Containers Software Servers Resource management Proposals Standards Testing

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Verification of the Effect of Label Modification on Neural Network Learning

Verification of the Effect of Label Modification on Neural N...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Tsubasa Oka Hiroaki Koga Dept. Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

This study focuses on the problem of subjective labeling that arises in the application of machine learning with neural networks to the medical field. The first problem is that of subjectivity, which arises because the labeling of medical data relies on expert knowledge and the process can be subjective. The second problem is the reduced information content of labels caused by discrete and quantitative labeling. If the intermediate values between the discrete values also have evaluative meaning, the detailed information is lost due to the discrete numerical labeling. We focus on such instability in labels and propose an approach to label modification using values inferred during neural network training. Specifically, we consider labels that are discrete, quantitative numbers as continuous numbers, compare the inferred value with the label value at each step in the learning phase, and compare the label value with the inferred value at each step in the learning phase. The update method is to give the label a sign-responsive variation. The goal is to modify each label using the value inferred by the inference made during learning in this way. As an experiment, we conducted an experiment on label modification under pseudo-conditions to verify its effectiveness. The results showed that when the amount of label modification was controlled by a constant, the generalization performance and the nature of label modification differed depending on the constant. In particular, generalization performance was improved when the constant of the label modification amount was determined so that the label value was separated from the inferred value at each step.

关键词： Training Neural networks Machine learning Labeling

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