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International Workshop on Robot Motion and control (RoMoCo)

作者： Gerardo Martínez-Terán Eduardo Bayro-Corrochano Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico Institute of Automatic Control and Robotics Poznan University of Technology

ISBN: (数字)9798350393965

ISBN: (纸本)9798350393972

Robotics and haptic systems have allowed new and diverse applications in the field of medicine, such as assisted surgery and teleoperation which have increasingly stringent requirements for accuracy, convergence, and low computational consumption. In this paper an adaptive PID control law (Proportional Integral Derivative controller, PID), of indirect architecture is presented for movement paths in a haptic system of open chain, where the identification of the plant is through a quaternionic wavelet neural network (Quaternion Wavelet Neural Network, QWNN) for tune the PID values, this allows the optimal movement into the regions of the workspace.

关键词： Uncertainty Quaternions Neural networks Surgery Robustness Haptic interfaces Topology

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Uncertainty Propagation in Stochastic Systems via Mixture Models with Error Quantification 63

Uncertainty Propagation in Stochastic Systems via Mixture Mo...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Figueiredo, Eduardo Patane, Andrea Lahijanian, Morteza Laurenti, Luca Tu Delft Delft Center for Systems and Control Netherlands Trinity College School of Computer Science and Statistics Dublin Ireland Cu Boulder Dept. of Aerospace Eng. Sciences and Computer Science United States

ISBN: (纸本)9798350316339

Uncertainty propagation in non-linear dynamical systems has become a key problem in various fields including control theory and machine learning. In this work, we focus on discrete-time non-linear stochastic dynamical systems. We present a novel approach to approximate the distribution of the system over a given finite time horizon with a mixture of distributions. The key novelty of our approach is that it not only provides tractable approximations for the distribution of a nonlinear stochastic system but also comes with formal guarantees of correctness. In particular, we consider the Total Variation (TV) distance to quantify the distance between two distributions and derive an upper bound on the TV between the distribution of the original system and the approximating mixture distribution derived from our framework. We show that in various cases of interest, including in the case of Gaussian noise, the resulting bound can be efficiently computed in closed form. This allows us to quantify the correctness of the approximation and to optimize the parameters of the resulting mixture distribution to minimize such distance. The effectiveness of our approach is illustrated on several benchmarks from the control community. © 2024 IEEE.

关键词： Stochastic systems

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Newton-Euler Modeling of Robot Dynamics Using Geometric Algebra

Newton-Euler Modeling of Robot Dynamics Using Geometric Alge...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Eduardo Bayro-Corrochano Daniel Alvarado-Mejia Institute of Automatic Control and Robotics Poznan University of Technology Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

In this work, we present the modeling of the dynamics of a robot manipulator using the Newton-Euler algorithm in the conformal algebra framework. The modeling of the dynamics of robot manipulators is currently done using the Euler-Lagrange formulation which is a batch type of computation. In contrast, in this paper, we propose a recursive algorithm for the modeling of the dynamics of robot manipulators using the Newton-Euler algorithm in the conformal geometric algebra framework.

关键词： Algebra Heuristic algorithms Computational modeling Optimal control Motors Real-time systems Mathematical models

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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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Deep Learning-Based Retinal Blood Vessel Segmentation Using U-Net Architecture

Deep Learning-Based Retinal Blood Vessel Segmentation Using ...

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E-Health and Bioengineering Conference (EHB)

作者： Ligia-Gabriela Boazu Marian-Alexandru Petraru Otilia Zvorișteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iași Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Retinal blood vessel segmentation is an essential component in the diagnosis and monitoring of various ophthalmological conditions, such as diabetic retinopathy, glaucoma or macular degeneration, providing valuable information about the state of blood vessels and ocular blood circulation. Traditional methods for segmenting blood vessels from retinal images present certain limitations in terms of accuracy and robustness, especially under variable lighting conditions, the presence of artifacts or low-quality images. However, current techniques based on convolutional neural networks have demonstrated the ability to achieve precise and robust segmentations in a variety of conditions, outperforming traditional methods. Nevertheless, neural networks face challenges regarding the limited availability of retinal image datasets necessary for training and evaluating these solutions. In this paper we describe a solution for retinal blood vessel segmentation using the U-Net architecture. This neural network achieves impressive results even with very small datasets, demonstrating the efficiency and robustness of the U-Net architecture for retinal blood vessel segmentation.

关键词： Training Macular degeneration Image segmentation Neural networks Blood vessels Network architecture Retina Robustness Monitoring Biomedical imaging

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Current-limiting control of interlinking converter to maintain power balance in hybrid microgrids

Current-limiting control of interlinking converter to mainta...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Skentzos, Panagiotis Konstantopoulos, George C. The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom University of Patras Dept. of Electrical and Computer Engineering Patra Greece

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

In this paper, a novel nonlinear current-limiting controller that maintains the desired power balance in a hybrid microgrid, is proposed for interlinking converters (ICs). The RMS value of the IC current is analytically proven to remain below a desired maximum value at all times using nonlinear ultimate boundedness theory, without limiting separately the d- and q-axis current components and without using adaptive saturation units, as done in conventional approaches. Furthermore, the stability of the closed loop system is investigated through root locus analysis for different values of the controller gain. Finally, the performance of the proposed control scheme is validated through detailed simulation results of an interlinking converter connected to both an AC and a DC subgrid. © 2022 IEEE.

关键词： controllers

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Enhancing Learning and Therapy for Children with Autism: Innovative Activities with the NAO Robot

Enhancing Learning and Therapy for Children with Autism: Inn...

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E-Health and Bioengineering Conference (EHB)

作者： Iustina-Bianca Bulai Otilia Zvorişteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Worldwide, autism affects 1 in 100 children, with diagnoses steadily rising since the 2000s. Romania lacks official statistics on autism prevalence, but global estimates suggest similarity. Children with autism struggle with social interactions and verbal communication, prompting interest in social robots for therapy and education. Tailored robot-assisted sessions offer potential for cognitive development, vocabulary enhancement, social interaction, and behavioral stimulation like concentration and attention. The NAO robot's user-friendly design, technical capabilities, and integrated features make it well-suited for these purposes. This paper presents activities that exemplify the concept of “learning through play,” allowing children to engage in exploration, experimentation, and effective learning in an enjoyable manner.

关键词： Autism Vocabulary Hospitals Social robots Education Biomedical engineering

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Cloud-Based Smart Home Monitoring using ThingSpeak and ESP32 5

Cloud-Based Smart Home Monitoring using ThingSpeak and ESP32

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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Komitov, Nikolay Terziyska, Margarita Terziyski, Zhelyazko University of Food Technologies Information and Control Technology Dept. of Automation Plovdiv Bulgaria University of Food Technologies Physics and Information Technologies Dept. of Mathematics Plovdiv Bulgaria Trakia University Stara Dept. of Computer Science and Mathematics Zagora Bulgaria

ISBN: (纸本)9798350352863

This paper presents an approach to implementing a cloud-based smart home monitoring system using the ESP32 microcontroller and ThingSpeak as the cloud platform. The proposed system provides an efficient solution for real-time monitoring of various environmental parameters, which are collected through sensors connected to the ESP32 and transmitted wirelessly to the ThingSpeak cloud. By leveraging the Internet of Things (IoT), this system enables users to remotely monitor their home environment from anywhere using a web interface. The article discusses the hardware setup, software implementation, and data visualization techniques, offering a practical guide for those interested in smart home technology and IoT integration. © 2024 IEEE.

关键词： Smart homes

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Comparative Analysis for System Modeling Using System Identification Techniques

Comparative Analysis for System Modeling Using System Identi...

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Electrical Engineering (ICEENG), 12th International Conference on

作者： Mayada Annan Mohamed Hassan Mahmoud Ashry Dept. Military Production Ministry Science Technology Excellent STCE Cairo Egypt Dept. Automatic Control Egyptian Armed Forces Cairo Egypt Dept. Automatic Control Arab Academy for Science Technology AAST Cairo Egypt

ISBN: (数字)9798350343427

ISBN: (纸本)9798350343434

System modelling is an essential task for controller design. System identification is widely used for dynamic systems modelling and provides high performance practical dynamic systems modelling. In this paper, a least square approach and recursive least square based identification techniques are proposed for comparative analysis of dynamic modelling of a single -input single-output tank process. Chirp and multi-sine signals are utilized for system modelling as they provide the required data for capturing the system dynamics. A comparative analysis is carried out with nonlinear recursive least square techniques such as ARX model, ARMAX model, Box-Jenkins model, Output-Error model for evaluating the proposed approach effectiveness. The ARX method provided high performance for single-input single-output tank system identification in the presence of system noise.

关键词： Analytical models Chirp Estimation Mean square error methods Systems modeling Mathematical models Data models

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Neuro-Symbolic Empowered Denoising Diffusion Probabilistic Models for Real-Time Anomaly Detection in Industry 4.0: Wild-And-Crazy-Idea Paper

Neuro-Symbolic Empowered Denoising Diffusion Probabilistic M...

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2023 Forum on Specification and Design Languages, FDL 2023

作者： Capogrosso, Luigi Mascolini, Alessio Girella, Federico Skenderi, Geri Gaiardelli, Sebastiano Dall'Ora, Nicola Ponzio, Francesco Fraccaroli, Enrico Di Cataldo, Santa Vinco, Sara Macii, Enrico Fummi, Franco Cristani, Marco Dept. of Engineering for Innovation Medicine University of Verona Italy Dept. of Control and Computer Engineering Polytechnic of Turin Italy Dept. of Regional and Urban Studies and Planning Polytechnic of Turin Italy Dept. of Computer Science University of North Carolina at Chapel Hill United States

ISBN: (纸本)9798350307375

Industry 4.0 involves the integration of digital technologies, such as IoT, Big Data, and AI, into manufacturing and industrial processes to increase efficiency and productivity. As these technologies become more interconnected and interdependent, Industry 4.0 systems become more complex, which brings the difficulty of identifying and stopping anomalies that may cause disturbances in the manufacturing process. This paper aims to propose a diffusion-based model for real-Time anomaly prediction in Industry 4.0 processes. Using a neuro-symbolic approach, we integrate industrial ontologies in the model, thereby adding formal knowledge on smart manufacturing. Finally, we propose a simple yet effective way of distilling diffusion models through Random Fourier Features for deployment on an embedded system for direct integration into the manufacturing process. To the best of our knowledge, this approach has never been explored before. copy;2023 IEEE. © 2023 IEEE computer Society. All rights reserved.

关键词： Industry 4.0

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