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作者： Yingjie Xiong Anna Wang Tao Zhang College Of Information Science and Engineering Northeastern University Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology

The sensor-less control system of PMSM is complicated,and it is of great significance to carry out accurate mathematical modeling and simulation *** is small in size,high in efficiency,and low in noise,so it is very popular in AC motor *** have been widely used in various electrical appliances such as machine tools,robots,and household *** order to reduce the high-frequency chatter of the sensor-less control strategy of permanent magnet synchronous motors,a sensor-less control method based on improved SMO is *** back-EMF component in the static coordinate system is obtained through the *** backEMF component undergoes closed-loop feedback to eliminate the high-frequency *** back-EMF component is calculated by an improved PLL to obtain the position and speed of the rotor to improve system *** the end of the article,the feasibility is proved by comparing it with the simulation of conventional SMO-PLL.

关键词： PMSM SMO with closed-loop feed back improved PLL

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Neuro-evolution of mobile robot controller 25

Neuro-evolution of mobile robot controller

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25th International Conference on Soft Computing, MENDEL 2019

作者： Sekaj, Ivan Cíferský, Ladislav Hvozdík, Milan Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia Institute of Informatics and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia

We present a neuro-evolution design for control of a mobile robot in 2D simulation environment. The mobile robot is moving in unknown environment with obstacles from the start position to the goal position. The trajectory of the robot is controlled by a neural network – based controller which inputs are information from several laser beam sensors. The learning of the neural network controller is based on an evolutionary approach, which is provided by genetic algorithm. © 2019, Brno University of Technology. All rights reserved.

关键词： Mobile robots

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Delivering Improved Care through Remote Health Monitoring Systems by Using Microservices. Case Study: Fall Detection Encompassed into Connected Care

Delivering Improved Care through Remote Health Monitoring Sy...

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International Conference on control Systems and Computer Science (CSCS)

作者： Marilena Ianculescu Adriana Alexandru Ionuţ-Emanuel Giura Ana-Mihaela Vasilevschi Communication Digital Applications and Systems Department National Institute for Research and Development in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Counselors Department National Institute for Research and Development in Informatics Târgovişte Romania Faculty of Electrical Engineering Electronics and Information Technology Târgovişte Romania Valahia University of Târgovişte Târgovişte Romania

Based on today’s modern technologies, patient care can be provided remotely, in a connected way, being, at the same time, personalized, patient-centered and proactive. Such an approach can be achieved using Remote Health Monitoring Systems (RHMS). In case of elderly people, dramatic permanent deteriorations of their health status can be caused by falls. The seniors’ health and life style monitoring and the detection and/or prevention of falls can be done by such RHMS, an example being the RO-SmartAgeing system developed inside “Non-invasive Monitoring System and Health Assessment of the Elderly in a Smart Environment (RO-SmartAgeing)” research project. The paper presents the problem of using microservices for optimizing the architecture and functionalities of RO-SmartAgeing system, and the way in which the problems of ensuring the security of patient data can be solved.

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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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Bias-free Parameter Identification for Non-Commensurable Fractional Systems

Bias-free Parameter Identification for Non-Commensurable Fra...

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European control Conference (ECC)

作者： Oliver Stark Martin Pfeifer Stefan Krebs Sören Hohmann Faculty of Electrical Engineering and Information Technology Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

This paper deals with the parameter identification for non-commensurable fractional systems under noisy observations of the output signal. Fractional systems are increasingly used to describe complex systems or memory effects. Actual identification methods can not handle noisy observations of the output signal if the system is not at rest. In this paper, an approach is proposed which uses a combination of the modulating function method and the instrumental variable method. The instrumental variable method yields unbiased estimates without knowing anything about the noise which corrupts the output signal. To calculate the instrumental variables, an algorithm to calculate the closed-form solution of a fractional system is also extended by the short-memory principle. The presented approach is compared to the common least-squares method by a numerical simulation.

关键词： Closed-form solutions Instruments Noise measurement Fractional calculus Time-domain analysis Splines (mathematics) Complex systems

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Robust Iterative Learning control for Spatially Interconnected Systems using 2D control Theory

Robust Iterative Learning Control for Spatially Interconnect...

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European control Conference (ECC)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Daniel Trzciński Eric Rogers Anton Kummert Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland Department of Electronics and Computer Science University of Southampton Southampton UK Faculty of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany

This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics modeled in the 2D systems setting to which existing results are not applicable. The first stage is to write the dynamics in 2D model form. Then the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This analysis results in a design algorithm that can be applied using linear matrix inequalities.

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Deep Learning Models for Intelligent Healthcare: Implementation and Challenges 7th

Deep Learning Models for Intelligent Healthcare: Implementat...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Rehman, Sadaqat ur Tu, Shanshan Shah, Zubair Ahmad, Jawad Waqas, Muhammad Rehman, Obaid ur Kouba, Anis Abbasi, Qammer H. Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Namal Institute Mianwali42250 Pakistan Department of Computer Science and Engineering Hammad Bin Khalifa University Doha Qatar School of Computing Edinburgh Napier University Edinburgh United Kingdom Department of Electrical Engineering Sarhad University of Science and IT Peshawar25000 Pakistan Department of Computer Science Prince Sultan University Riyadh Saudi Arabia James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom

ISBN: (纸本)9783030786083

The rapid developments of artificial intelligent (AI) is being transformed for its extensive use-cases, people-centered intelligent systems focusing on care delivery, research encounter complex problems related to improve the overall infrastructure and management of intelligent delivery service;for instance, bringing transformation in healthcare sector for monitoring patients with chronic disease. Most of these systems are driven by state-of-the-art learning algorithms i.e., Convolution Neural Network. The CNN algorithm is considered to be one of the most prominent architectures of DL. Recently, due to enormous growth in the amount of annotated data and the development of CNN hardware accelerator, further, boost the research on CNN and accomplished benchmark enactment on different applications. This paper presents cutting-edge applications of CNN for an intelligent healthcare system. We provide useful findings of different CNN features such as optimization, fast computation, design, activation function, and loss function. To our knowledge, this is the first comprehensive work to address the recent trends in the architecture of CNN, which offers insight to the underlying problems and provides the potential solutions for any given intelligent healthcare applications. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

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Preface

Lecture Notes in Networks and Systems

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Lecture Notes in Networks and Systems 2024年 1076 LNNS卷 v-vii页

作者： Biele, Cezary Kacprzyk, Janusz Kopeć, Wieslaw Możaryn, Jakub Owsiński, Jan W. Romanowski, Andrzej Sikorski, Marcin National Information Processing Institute Warszaw Poland Polish Academy of Sciences Systems Research Institute Warsaw Poland Polish-Japanese Academy of Information Technology Warsaw Poland Institute of Automatic Control and Robotics Faculty of Mechatronics Warsaw University of Technology Warsaw Poland Institute of Applied Computer Science Faculty of Electrical Electronic Computer and Control Engineering Lódż University of Technology LODZ Poland Department of Applied Informatics in Management Faculty of Management and Economics Gdańsk University of Technology Gdańsk Poland

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Revealing preference in popular music through familiarity and brain response

arXiv

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arXiv 2021年

作者： Sangnark, Soravitt Autthasan, Phairot Ponglertnapakorn, Puntawat Chalekarn, Phudit Sudhawiyangkul, Thapanun Trakulruangroj, Manatsanan Songsermsawad, Sarita Assabumrungrat, Rawin Amplod, Supalak Ounjai, Kajornvut Wilaiprasitporn, Theerawit Bio-inspired Robotics and Neural Engineering Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand Vision and Learning Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand School of Energy Science and Engineering Vidyasirimedhi Institute of Science & Technology Rayong Thailand Biological Engineering program Faculty of Engineering Neuroscience Center for Research and Innovation Learning Institute King Mongkut’s University of Technology Thonburi Thailand Faculty of Electrical Engineering Sirindhorn International Institute of Technology Thammasat University Thailand School of Engineering Tohoku University Japan

Music preference was reported as a factor, which could elicit innermost music emotion, entailing accurate ground-truth data and music therapy efficiency. This study executes statistical analysis to investigate the distinction of music preference through familiarity scores, response times (response rates), and brain response (EEG). Twenty participants did self-assessment after listening to two types of popular music’s chorus section: music without lyrics (Melody) and music with lyrics (Song). We then conduct a music preference classification using a support vector machine, random forest, and k-nearest neighbors with the familiarity scores, the response rates, and EEG as the feature vectors. The statistical analysis and F1-score of EEG are congruent, which is the brain’s right side outperformed its left side in classification performance. Finally, these behavioral and brain studies support that preference, familiarity, and response rates can contribute to the music emotion experiment’s design to understand music, emotion, and listener. Not only to the music industry, the biomedical and healthcare industry can also exploit this experiment to collect data from patients to improve the efficiency of healing by music. © 2021, CC BY-NC-ND.

关键词： Decision trees

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The Inherent Velocity Limitation in Robust Robot control

The Inherent Velocity Limitation in Robust Robot Control

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International Carpathian control Conference (ICCC)

作者： Ján Kardoš Institute of Robotics and Cybernetics Faculty of Electrical Engineering Information Technology Slovak University of Technology in Bratislava Bratislava Slovak Republic

ISBN: (数字)9781728119519

ISBN: (纸本)9781728119526

The aim of this paper is to show an original method of the velocity limitation in robust MIMO motion system based on the theory of variable structure control. The advantage of the presented approach is in its usability for both the fixed target control and the command following one. Furthermore, we provide a continuous modification of the control algorithm suitable for engineering practice, where the motion velocity limitation for the safety and integrity of the technology is required. Numeric simulation on the robot dynamic model illustrates the quality and the reliability of the presented control method.

关键词： Switches control systems Robots Numerical models Heuristic algorithms Torque Mathematical model

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