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A sliding mode controller design for thermal comfort in buildings

engineering Transactions 2019年第4期67卷 475-489页

作者： Skruch, Pawel Dlugosz, Marek AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Al. Mickiewicza 30 Kraków30-059 Poland

One of the factors determining comfort in buildings is the indoor air temperature of the rooms. A control system, part of the home automation system, should stabilise air temperature to the desired level, despite various disturbances such as the presence of random or occasional sources of heat. Inaccurate models of the dynamics of air temperature changes in buildings prescribe the use of robust control methods, a type of which is the sliding mode controller. This article presents the application of a sliding mode controller (SMC) to home automation systems, designed to control air temperature inside a building. The sliding-mode controller makes use of sliding surfaces, which are defined by the assumed trajectory and the system output. The control law is designed in such a way that the trajectory of the system tends to the sliding surface from any initial point and remains on it after reaching the sliding surface. In this article, a model at air temperature change dynamics inside a building is presented. The modelling approach relies on the lumped-parameter methodology, in which distributed physical properties are represented by lumped parameters (such as thermal capacity or resistance). The model takes into account the loss of heat through conduction and ventilation, as well as internal heat gain. The parameters of the model can be obtained easily from the thermal properties of the construction materials. Theoretical considerations were applied in simulation experiments and the results of these experiments confirm the performance improvement achieved by the proposed solutions. © 2019, Polish Academy of Sciences. All rights reserved.

关键词： Atmospheric temperature

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IoT enabled temperature sensing system of molten metal in welding

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Materials Today: Proceedings 2021年 45卷 2514-2517页

作者： S. Sanjith N. Balaji L.D. Vijay Anand W. Regis Anne P. Shanmugapriya S. Sheeba Rani Department of Computer Science St. Alphonsa College of Arts and Science Soosaipuram 629157 Tamilnadu India Department of Instrumentation and Control Engineering Sri Sairam Engineering College Chennai 600044 Tamilnadu India Department of Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore 641114 Tamilnadu India Department of Computer Applications Sri Krishna College of Engineering and Technology Coimbatore 641008 Tamilnadu India Department of Electrical and Electronics Engineering Sri Sairam Engineering College Chennai 600044 Tamilnadu India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore 641008 Tamilnadu India

The control of temperature in welding is essential to maintain the quality of metal joints. Due to current fluctuations and instrument errors, the quality of joint may be affected. The excess of temperature or molten stage may leads to change the effect of micro structure. An automatic temperature sensing system is needed to eliminate this problem. It is fulfilled through Internet of Things (IoT) based temperature sensing on molten metal in welding. The temperature sensors, micro controller, LAN/Wireless communications and server are used to enhance the automatic temperature sensing on molten metal in welding process. The experimentation is conducted on arc welding of mild steel. The quality characteristics and optimization studied through Taguchi method.

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Hardware-in-the-Loop Simulation Testbed for Three-Axis Earth's Magnetic Field Generation Based on 2.4- Meter Square Helmholtz Coils

Hardware-in-the-Loop Simulation Testbed for Three-Axis Earth...

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IEEE Symposium on Position Location and Navigation (PLANS)

作者： Jormpon Chaisakulsurin Shariff Manuthasna Tanawish Masri Thanayuth Panyalert Kritsada Palee Pakawat Prasit Patcharin Kamsing Peerapong Torteeka Thai Space Consortium Project National Astronomical Research Institute of Thailand (Public Organization) Chiang-Mai Thailand Center of Observatory Operation and Engineering National Astronomical Research Institute of Thailand (Public Organization) Chiang-Mai Thailand Faculty of Engineering Program in Robotics and Computational Intelligence Systems International Academy of Aviation Industry King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Aeronautical Engineering Air-Space Control Optimization and Management Laboratory International Academy of Aviation Industry King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

This paper proposes a Hardware-in-the-Loop sim-ulation (HiLs) tested via square Helmholtz coils as a relative magnetic field generator. In technical terms, the HiLs is an indispensable tool for engineering design during rapid proto-typing of attitude determination and control algorithms for the turning parameters that control the attitude of the satellite, since most of the satellite's mission relies on its attitude, making this system one of the most essential to the satellite's operation. More-over, performing controlled experiments with the parameters for developing adaptive control algorithms improves the overall efficiency of the satellite's kinematic system. The conceptual design of a proposed system architecture can be composed of the electrical currents of 2.4-meter square Helmholtz coils produced by a low-level microcontroller equipped with a DC-motor driver by a pulse-width modulation (PWM) signal through real-time connection to an orbit propagator using a high-level computer. This research focuses on the attitude dynamic of satellites through the interaction between the Earth's magnetic field (EMF) and the magnetotorque in the satellite. To apply this phenomenon, the intensity and the direction of the magnetic field must be identified through Biot-Savart's law. Along with the EMF, the reference position is calculated using the standard general perturbations satellite orbit model (SGP4), and the intensity is modeled based on coefficients from the 13 th edition of the International Geo-magnetic Reference Field (IGRF). Therefore, this paper presents a detailed development of a HiLs testbed for distributed attitude determination and control systems (hardware and software co-design, protocol, and control theory). Furthermore, it discusses a classic cooperative control case for the output of magnetic field intensity and direction, which was undertaken to explain the integrated simulation process and validate the effectiveness of the co-simulation tested to be

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Anomaly Detection of Marine Diesel Engine Valve System based on Mahalanobis Distance

Anomaly Detection of Marine Diesel Engine Valve System based...

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2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Sun, Yue Xu, Aidong Wang, Kai Jia, Shuli Guo, Haifeng Han, Xiaojia Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China Automation Engineering Department Shanghai Marine Diesel Engine Research Institute Shanghai China

ISBN: (纸本)9781728159454

Diesel engine is an important energy equipment. The valve system is the core component of diesel engine with high failure rate. It is of great significance to study the abnormal detection method of the diesel engine valve system and realize the failure warning before the failure occurs for avoiding the unexpected shutdown of the diesel engine. In this paper, an anomaly detection method of marine diesel engine valve system based on Mahalanobis distance (MD) is proposed. The failure mode of diesel engine system is analyzed. Three thermal parameters are selected as monitoring parameters for the failure mode of roller fragmentation. Fault features are extracted by MD method and the failure threshold is determined by Box-Cox transformation. Finally, the effectiveness of the proposed method is verified by the durability test of diesel engine. © 2020 IEEE.

关键词： Diesel engines

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Optimized 3D Drone Placement and Resource Allocation for LTE-Based M2M Communications

Optimized 3D Drone Placement and Resource Allocation for LTE...

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IEEE Conference on Vehicular Technology (VTC)

作者： Ahmed Fahim Yasser Gadallah Robotics Control and Smart Systems Department of Electronics and Communications Engineering The American University in Cairo New Cairo Egypt

ISBN: (数字)9781728152073

ISBN: (纸本)9781728140537

The deployment of drone-mounted communication systems has received increasing interest and attention recently as it allows significant improvement to the network access capacity and coverage. Many applications can benefit from such deployments in particular machine-to-machine (M2M) communications. In this study, we propose a technique for the rapid deployment of an LTE drone-mounted base station to serve a group of machine-type-communication devices (MTCDs) that are deployed in disaster situations or within remote applications. The objective is to maximize the number of served MTCDs while meeting their transmission delay requirements. This results in optimizing the 3D placement of the drone base station as well as the allocation of the available communication resources. We evaluated the proposed technique through several simulation experiments. The simulation results demonstrate significant improvement in the aggregate system throughput and the overall system deadline missing performance along with the increased number of served MTCDs compared to other drone placement approaches.

关键词： Drones Base stations Machine-to-machine communications Three-dimensional displays Optimization Quality of service Resource management

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Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

arXiv

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： robotics

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Influence of the variables describing brain signals on the performance of the Naive Bayesian Classifier

Influence of the variables describing brain signals on the p...

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Progress in Applied Electrical engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Jaroslaw Zygarlicki Adam Lysiak Barbara Grochowicz Mariusz Pelc Waldemar Bauer Dawid Baczkowicz Krzysztof Krecisz Katarzyna A. Dylag Wiktoria Wieczorek Radana Kahankova Radek Martinek Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland School of Computing and Mathematical Sciences University of Greenwich London UK Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland St. Louis Children Hospital Krakow Poland Department of Pathophysiology Jagiellonian University in Krakow–Collegium Medicum Krakow Poland Department of Bioinformatics and Telemedicine Jagiellonian University in Krakow–Collegium Medicum Krakow Poland Department of Cybernetics and Biomedical Engineering–FEECS VSB—Technical University Ostrava Ostrava–Poruba Czech Republic

ISBN: (数字)9781665455152

ISBN: (纸本)9781665455169

In this paper various variables describing brain signals such as near-infrared spectroscopy (NIRS) and electroencephalography (EEG) on the Naive Bayesian Classifier were presented. Analysis of biomedical signals is a very challenging task – therefore the authors of this work decided to analyse two types of brain signals – EEG and NIRS, which have different features, character, nature and are differently prone to various artifacts occurrence. The applied classifiers can be applied for various features extraction and pattern comparisons, which is useful in diagnostic processes.

关键词： Electrical engineering Feature extraction Electroencephalography Bayes methods Task analysis Functional near-infrared spectroscopy

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Deep Learning-based Algorithm for Mobile Robot control in Textureless Environment

Deep Learning-based Algorithm for Mobile Robot Control in Te...

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Mechatronics Systems and Materials (MSM)

作者： Milica Petrović Arkadiusz Mystkowski Aleksandar Jokić Lazar Đokić Zoran Miljković Production Engineering Department University of Belgrade Belgrade Serbia Department of Automatic Control and Robotics Bialystok University of Technology Bialystok Poland

ISBN: (数字)9781728169569

ISBN: (纸本)9781728169576

For the implementation of stereo image-based visual servoing algorithm in the eye-in-hand robotics applications, one of the main concerns is the accurate point feature detection and matching algorithm. Since the visual servoing is carried out in the textureless environment, the feature detection process is even more challenging. To fulfill the requirement of a robust and reliable point feature detection process, in this paper we present the novel deep learning-based algorithm. The approach based on convolutional neural networks and algorithm for detection of manufacturing entities is proposed and detected regions of interest are utilized for the improvement of the point feature detection algorithm. The proposed algorithm is experimentally evaluated in real-world settings by using wheeled nonholonomic mobile robot RAICO equipped with stereo vision system. The experimental results show the improvement of 58% in the accuracy of matched point features in the images obtained during the visual servoing process. Moreover, with the implementation of the proposed deep learning-based approach, the number of successful experimental runs has increased by 80%.

关键词： Feature extraction Mobile robots Visual servoing Manufacturing Classification algorithms Cameras

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FreeDriveRF: Monocular RGB Dynamic NeRF without Poses for Autonomous Driving via Point-Level Dynamic-Static Decoupling

arXiv

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arXiv 2025年

作者： Wen, Yue Song, Liang Liu, Yijia Zhu, Siting Miao, Yanzi Han, Lijun Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Dimanshen Technology Co. Ltd. China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China

Dynamic scene reconstruction for autonomous driving enables vehicles to perceive and interpret complex scene changes more precisely. Dynamic Neural Radiance Fields (NeRFs) have recently shown promising capability in scene modeling. However, many existing methods rely heavily on accurate poses inputs and multi-sensor data, leading to increased system complexity. To address this, we propose FreeDriveRF, which reconstructs dynamic driving scenes using only sequential RGB images without requiring poses inputs. We innovatively decouple dynamic and static parts at the early sampling level using semantic supervision, mitigating image blurring and artifacts. To overcome the challenges posed by object motion and occlusion in monocular camera, we introduce a warped ray-guided dynamic object rendering consistency loss, utilizing optical flow to better constrain the dynamic modeling process. Additionally, we incorporate estimated dynamic flow to constrain the pose optimization process, improving the stability and accuracy of unbounded scene reconstruction. Extensive experiments conducted on the KITTI and Waymo datasets demonstrate the superior performance of our method in dynamic scene modeling for autonomous driving. Our implementation will be available at https://***/IRMVLab/FreeDriveRF. Copyright © 2025, The Authors. All rights reserved.

关键词： Optical flows

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Cover Image, Volume 40, Number 6, September 2023

引用

Journal of Field robotics 2023年第6期40卷

作者： Guoteng Zhang Shugen Ma Jinguo Liu Xianwu Zeng Lingyu Kong Yibin Li School of Control Science and Engineering Shandong University Jinan China Department of Robotics Ritsumeikan University Shiga Japan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Yibin Li School of Control Science and Engineering Shandong University Jinan China. Intelligent Robot Research Centre Zhejiang Lab Hangzhou China

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