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International computer Sciences and Information Technologies (CSIT)

作者： Nataliia Lutska Lidiia Vlasenko Nataliia Zaiets Vitaliy Lysenko dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350334326

Relevant today is the digitalization of industrial enterprises, which is an evolutionary continuation of the introduction of MES/MOM. At the same time, an important role is played by the construction of mathematical models for various purposes, which are the main component of the Digital Twin development. Digital Twin provides a new philosophy for conducting enterprise production processes based on these models, which is aimed at improving the efficiency of both individual sectors and the enterprise as a whole. To increase the profit of the enterprise, it is necessary to ensure the planned productivity of technological processes, the final indicator of which is the yield of sugar. Taking into account that a significant number of material flows operate at the enterprise, only production flows with which the operator-technologist works are singled out in the work. The selected flows, based on expert assessments, were assigned weighted values of the impact on the overall performance of the sugar production. This made it possible to build a mathematical model that predicts the yield of sugar from input flows. The structure and parameters of this model are determined by machine learning methods. This is a feed-forward neural network MLP 7-23-23-1, which provides forecast accuracy with an error of less than 1%. The model can be used to model, correct, and predict the process conditions of an enterprise, which will increase the overall productivity of the sugar factory.

关键词： Productivity Biological system modeling Machine learning Predictive models Mathematical models Sugar industry Production facilities

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Direct data-driven LPV control of nonlinear systems: An experimental result

arXiv

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arXiv 2022年

作者： Verhoek, Chris Abbas, Hossam S. Tóth, Roland Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven5600MB Netherlands Institute for Electrical Engineering in Medicine Universität zu Lübeck Lübeck23558 Germany Systems and Control Lab Institute for Computer Science and Control Budapest1111 Hungary

We demonstrate that direct data-driven control of nonlinear systems can be successfully accomplished via a behavioral approach that builds on a Linear Parameter-Varying (LPV) system concept. An LPV data-driven representation is used as a surrogate LPV form of the data-driven representation of the original nonlinear system. The LPV data-driven control design that builds on this representation form uses only measurement data from the nonlinear system and a priori information on a scheduling map that can lead to an LPV embedding of the nonlinear system behavior. Efficiency of the proposed approach is demonstrated experimentally on a nonlinear unbalanced disc system showing for the first time in the literature that behavioral data-driven methods are capable to stabilize arbitrary forced equilibria of a real-world nonlinear system by the use of only 7 data points. © 2022, CC BY-NC-SA.

关键词： Nonlinear systems

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Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder

arXiv

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arXiv 2022年

作者： van Haren, Max Poot, Maurice Kostić, Dragan van Es, Robin Portegies, Jim Oomen, Tom Control Systems Technology Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands ASM Pacific Technology Centre of Competency Beuningen Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands Delft Center for Systems and Control Delft University of Technology Delft Netherlands

Mechatronic systems have increasingly stringent performance requirements for motion control, leading to a situation where many factors, such as position-dependency, cannot be neglected in feedforward control. The aim of this paper is to compensate for position-dependent effects by modeling feedforward parameters as a function of position. A framework to model and identify feedforward parameters as a continuous function of position is developed by combining Gaussian processes and feedforward parameter learning techniques. The framework results in a fully data-driven approach, which can be readily implemented for industrial control applications. The framework is experimentally validated and shows a significant performance increase on a commercial wire bonder. © 2022, CC BY.

关键词： Gaussian distribution

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Assessment of Integrating Evacuated Tube-Based Domestic Electric/Solar Water Heater with an Aluminum Reflector for Managing Electrical Consumption

SSRN

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SSRN 2023年

作者： Sabry, Ahmad H. Al-Dujaili, Ayad Q. Oleiwi, Bushra Kadhim Alkubaisi, Yaser Mahmood Humaidi, Amjad J. Electrical Engineering Technical College Middle Technical University Baghdad Iraq Department of Control and Systems Engineering University of Technology-Iraq Baghdad Iraq Department of Computer Engineering Al-Nahrain University Al Jadriyah Bridge Baghdad64074 Iraq Department of Sustainability Management Dubai Academic Health Corporation Dubai4545 United Arab Emirates Control and Systems Eng. Dept. University of Technology Baghdad Iraq

Most places in the world have seen rapid increases in the need for power. It is essential to look for alternatives and energy-saving technologies because traditional fossil fuel power plants emit pollution in addition to the electricity they produce. This work considers a multi-generational heating system with the hybrid Electric/Solar Water Heaters (ESWHs) to replace electric water heaters (EWH)by combining the ESWH with an Aluminum reflector. This work experimental discusses the performance of the ESWH and the influence of placing a reflector plate underneath the evacuated tubes in Baghdad-Iraq. A test procedure to heat the water to a specified heating temperature over the whole day period was conducted to analyze the daily power consumption profile of the system. Four operational scenarios have been conducted including the mode;the ESWH as a solar water heater, ESWH as an electric water heater, ESWH without a reflector, and ESWH with a reflector plate. The experimental analysis confirmed that the presented multi-generational heating configuration could contribute to energy sustainably. The developed multi-generational heating system achieved an improvement in annual energy consumption of 15.4% over the hybrid electric/solar water heater and 46.2% over the traditional electrical water heater. © 2023, The Authors. All rights reserved.

关键词： Energy conservation

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Implementation of a home appliance mobile platform based on computer vision: System configuration and calibration

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2020年第4期82卷 41-54页

作者： Secuianu, Florin-Dan Lupu, Ciprian Dept. of Automatic Control and Systems Engineering University POLITEHNICA of Bucharest Romania

This paper is a continuation of our previous studies on the implementation of a mobile platform based on computer vision and Raspberry Pi hardware, precise indoor navigation. Thus, we implemented a prototype version of a robot that can recognize targets using machine learning and computer vision based algorithms. Further, the platform was improved to achieve complete autonomy, indoor mapping and navigation, and self-charging. We showed that it is possible to create an affordable, completely autonomous robot that can navigate and detect targets. The present study has two main objectives. The first one is to build a platform that uses computer vision algorithms to detect objects, processes and aggregates the information acquired from various sensors, shares it with other devices, and has capabilities of remote and automated reconfiguration of the main program loop and logging results. The second objective is to improve the precision of the localization and navigation by adjusting the data received from the digital compass to the specifics of the environment and the hardware setup of the mobile unit. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Python

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Validation of a two-wheel vehicle model using Genetic Algorithm

Validation of a two-wheel vehicle model using Genetic Algori...

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International Symposium on Computational Intelligence and Informatics

作者： Attila Widner Balázs Varga Dániel Medgyesi Tamás Tettamanti Dept. of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Fac. of Transportation Engineering and Vehicle Engineering Budapest Hungary Dept. of Innovative Vehicles and Materials John von Neumann University GAMF Fac. of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350398830

Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.

关键词： Industries computer science Mechatronics Machine learning algorithms Computational modeling Vehicle dynamics Usability

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The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

The Goldilocks Framework: Towards Selecting the Optimal Appr...

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AI engineering - Software engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Rimman Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies’ industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.

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Mathematical Model of a Three-Phase Induction Motor with Asymmetrical Twelve-Zone Stator Windings 4

Mathematical Model of a Three-Phase Induction Motor with Asy...

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4th IEEE International Conference on Modern Electrical and Energy System, MEES 2022

作者： Tytiuk, Valerii Chornyi, Oleksii Busher, Victor Siverskaya, Tatyana Baranovskaya, Mila Kuznetsov, Vitalii Njsc 'Karaganda Industrial University' Department 'Artificial Intelligence Technologies' Temirtau Kazakhstan Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine National University 'Odessa Maritime Academy' Dept. of Electrical Engineering and Electronics Odessa Ukraine Njsc 'Karaganda Industrial University' Department 'Power Engineering' Temirtau Kazakhstan Kryvyi Rih National University Department of Electromechanics Kryvyi Rih Ukraine Ukrainian State University of Science and Technologies Department of the Electrical Engineering Dnipro Ukraine

ISBN: (纸本)9798350346831

The paper proposes a mathematical model of a three-phase induction motor with an asymmetrical twelve-zone winding of stator with parallel connection of subwindings. The mathematical model was developed using the theory of generalized electromechanical converter and contains equations of electrical equilibrium of six stator windings and three rotor windings. The equations for calculating the electromagnetic moment and the equations of motion of the induction motor with an asymmetrical twelve-zone stator winding rotor were obtained. The developed mathematical model in the form of cell-matrix equations has been implemented in MATLAB/Simulink. © 2022 IEEE.

关键词： Induction motors

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Challenges in developing and deploying AI in the engineering, procurement and construction industry

Challenges in developing and deploying AI in the engineering...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Rimma Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

AI in the engineering, Procurement and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Several research papers exist describing the potential of AI, and many surveys and white papers have been published indicating the challenges of AI deployment in the EPC industry. However, there is a recognizable shortage of in-dept. studies of deployment experience in academic literature, particularly those focusing on the experiences of EPC companies involved in large-scale project execution with high safety standards, such as the petrochemical or energy sector. The novelty of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

关键词： Industries Procurement Companies Manuals Petrochemicals Software Safety

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

引用

IEEE Symposium on Network Operations and Management

作者： Árpád Somogyi Tamás Tettamanti Pál Varga Zsolt Szalay Dániel Baranyai Tamás Lovas Dept. of Photogrammetry and Geoinformatics Fac. of Civil Engineering Budapest University of Technology and Economics Budapest Hungary Systems and Control Laboratory Institute for Computer Science and Control of the Eötvös Loránd Research Network Budapest Hungary Dept. of Telecommunications and Media Informatics Fac. of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Dept. of Automotive Technologies Fac. of Transportation Eng. and Vehicle Eng. Budapest University of Technology and Economics Budapest Hungary

One major goal of digital twin technology applied in the Architecture, engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated.

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