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arXiv 2024年

作者： Besançon, Gildas Cristofaro, Andrea Ferrante, Francesco Univ. Grenoble Alpes CNRS Grenoble INP GIPSA-lab Grenoble France Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Engineering University of Perugia Italy

The problem of estimating the reaction coefficient of a system governed by a reaction-diffusion partial differential equation is tackled. An estimator relying on boundary measurements only is proposed. The estimator is based upon a setpoint regulation strategy and leads to an asymptotically converging estimate of the unknown reaction coefficient. The proposed estimator is combined with a state observer and shown to provide an asymptotic estimate of the actual system state. A numerical example supports and illustrates the theoretical results. © 2024, CC BY-NC-SA.

关键词： Uncertainty analysis

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Exploring the use of deep learning in task-flexible ILC*

Exploring the use of deep learning in task-flexible ILC*

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American control Conference (ACC)

作者： Anantha Sai Hariharan Vinjarapu Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Hungary

Growing demands in today’s industry results in increasingly stringent performance and throughput specifications. For accurate positioning of high-precision motion systems, feedforward control plays a crucial role. Nonetheless, conventional model-based feedforward approaches are no longer sufficient to satisfy the challenging performance requirements. An attractive method for systems with repetitive motion tasks is iterative learning control (ILC) due to its superior performance. However, for systems with non-repetitive motion tasks, ILC is generally not applicable, despite of some recent promising advances. In this paper, we aim to explore the use of deep learning to address the task flexibility constraint of ILC. For this purpose, a novel Task Analogy based Imitation Learning (TAIL)-ILC approach is developed. To benchmark the performance of the proposed approach, a simulation study is presented which compares the TAIL-ILC to classical model-based feedforward strategies and existing learning-based approaches, such as neural network based feedforward learning.

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Prediction of Heat Transfer in Smart Buildings using Internet of Things based Artificial Intelligence 3

Prediction of Heat Transfer in Smart Buildings using Interne...

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3rd International Conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Rehman, TasneemBano Madiajagan, M. Ramya, D. Saratha, M. Mohan Krishna, P.B. Kumar, Prashant Sage University Department of Computer Science and Engineering Madhya Pradesh Bhopal India Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Vellore India Sathyabama Institute of Science and Technology Department of Eee Tamil Nadu Chennai India M.Kumarasamy College of Engineering Department of Mca Tamil Nadu Karur India National Institute of Technology Department of Process Control Telangana Warangal India Lovely Professional University Department of Chemical Engineering Punjab India

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

With rapid growth and a higher standard of living, the demand for usable energy has increased tremendously over the last few decades, with the construction industry being one of the most notable examples. The energy efficiency of a building is influenced by a variety of factors, including the weather in the area, the structure characteristics, and how people use electricity. These algorithms can be used to generate a prediction model for smart building indoor temperature forecasting using the Internet of Things and several commonly used artificial intelligence algorithms, which can then be used to generate a prediction model for smart building outdoor temperature forecasting. It was necessary to employ freely accessible software tools in order to make geometric and sensory data available in a virtual reality application and to build the PMV and PPD indices. On a low-cost edge computing device, semi-automatic analysis of streaming thermal images from a non-intrusive sensor was performed in order to offer near real-time Mean Radiant Temperature (MRT)estimations. An experimental space that had been mechanically preconditioned was filled with a dynamic temperature environment, and a prototype of the system was employed in a series of trials. Results show that the data backs up the fact that the system output and the heat sensations felt under different settings are consistent. © 2022 IEEE.

关键词： Application programs

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Proposal of high attenuating external magnetic field chamber for biological experiments

Proposal of high attenuating external magnetic field chamber...

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International Conference on Computational Problems of Electrical engineering (CPEE)

作者： Marek Bajtoš Robert Cichorowski Roman Radil Ladislav Janoušek Department of Electromagnetic and Biomedical Engineering Faculty of Electrical Engineering and Informational Technology Žilina Slovakia Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (数字)9798331506643

ISBN: (纸本)9798331506650

This work presents the design, construction, and validation of a chamber for magnetic field attenuation. Needs of magnetic background controlling during experiments focused on behavior of biological samples exposed to various levels of the low frequency time-varying magnetic field set the motivation for this work. The solution is proposed with regard to the correct cultivation conditions of microbiological samples. The chosen methodology is established on the means of numerical modeling and simulations, as well as 3D printing techniques. The design process incorporates computer-aided design (CAD) software for the chamber proposal, subsequent printing via a 3D printer, followed by the construction of an attenuating chamber using mu-metal foil. The validation process involves measurements of magnetic flux density within the chamber, and comparison thereof with numerical simulations performed via CST Design Studio. All the solution steps resulted in a valid and effective magnetic field attenuation chamber, suitable for use in laboratory conditions.

关键词： Solid modeling Time-frequency analysis Design automation Three-dimensional displays Computational modeling Attenuation Three-dimensional printing Numerical models Magnetic fields Proposals

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An Integrated Environment for the Reliability Assessment of CNNs Accelerators Implemented in FPGAs

An Integrated Environment for the Reliability Assessment of ...

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Latin American Test Workshop, LATW

作者： Luis Ariel Mesa Juan-David Guerrero-Balaguera Erika D. Castañeda Ernesto Sanchez Wilson-Javier Pérez-Holguín GIRA Research Group Universidad Pedagogica y Tecnologica de Colombia (UPTC) Department of Control and Computer Engineering (DAUIN) Politecnico di Torino

ISBN: (数字)9798350365559

ISBN: (纸本)9798350365566

This work presents the development of an integrated framework that facilitates the resilience evaluation of CNNs w.r.t. hardware faults by resorting to fault emulation strategies. The proposed framework leverages the flexibility of Field-Programmable Gate-Arrays (FPGAs) to implement and evaluate any DL accelerator architecture. In addition, we describe the detailed procedure to emulate faults inside a DL architecture. We report the cost, simulation time, and hardware overhead required by the proposed technique when using a stream-processing DL accelerator to deploy some of the most relevant layers of LeNet5. The experimental results were gathered in four different FPGA-based platforms, demonstrating the flexibility of the proposed approach.

关键词： Costs Emulation Accelerator architectures Life estimation Logic gates Hardware Reliability

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Artificial Intelligence Based Employee Attrition Analysis and Prediction

Artificial Intelligence Based Employee Attrition Analysis an...

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Computing and Informatics (ICCI), International Conference on

作者： Nazli Sila Ozakca Ali Bulus Aydin Cetin Havelsan Inc. Command Control and Defence technologies Ankara Turkiye Computer Engineering Department Faculty of Technology Gazi University Ankara Turkiye

The use of classification models to predict the probability of an employee leaving the job can greatly improve the ability of human resources to intervene in a timely manner and rectify the situation to prevent attrition. After the so-called “The Great Resignation”, which took place after the pandemic period, studies on attrition have increased in order to regain the lost workforce and increase the loyalty of existing employees. In Turkey, however, studies in this field remain insufficient. The aim of this study is to predict the possible loss of employees, to take relevant measures and to reduce the financial losses of companies. The study was made available as SaaS (Software as a Service) based in order to facilitate accessibility to the target audience. For the analysis phase, the columns in the data set were analyzed with Pandas and Scikit-Learn library. Exploratory Data Analysis was performed by visualizing the analyzed data with Plotly and Seaborn libraries. Various insights were obtained with these inferences. The data was subjected to pre-processing stages such as cleaning, missing data completion, scaling, feature selection, data set balancing, dimension reduction, etc. to make it useful. Logistic Regression, KNN, SVM, Desicion Tree, Random Forest, ADABoost and Naive Bayes were used to train the model. In order to enrich the data set and increase the efficiency of the model, artificial intelligence-based synthetic data generation (Data Augmentation) was performed. In case of missing columns in the trained model, KNN-Data Imputation, one of the missing data completion methods, was used. In the optimization process of the model, hyperparameter optimizations were performed to achieve maximum efficiency with improvements. 5-fold crossvalidation prevented the model from over-learning. Performance was analyzed on the basis of Accuracy, Recall, Precision and F1-score metrics and the success criterion was determined as F1-Score. The model was presented as a web ser

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Multi-talker Verbal Interaction for Humanoid Robots

Multi-talker Verbal Interaction for Humanoid Robots

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

作者： Bartlomiej Klin Ryszard Beniak Michal Podpora Arkadiusz Gardecki Joanna Rut Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Department of Computer Science Opole University of Technology Faculty of Production Engineering and Logistics Opole University of Technology

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

Working in multi-talker mode is viable under certain conditions, such as the fusion of audio and video stimuli along with smart adaptive beamforming of received audio signals. In this article, the authors verify part of the researched novel framework, which focuses on adapting to dynamic interlocutor’s location changes in the engagement zone of humanoid robots during the multi-talker conversation. After evaluating the framework, the authors confirm the necessity of a complementary and independent method of increasing the interlocutor’s signal isolation accuracy. It is necessary when video analysis performance plummets. The authors described the leading cause as insufficient performance during dynamic conversations. The video analysis cannot derive a new configuration when the interlocutor’s speech apparatus moves beyond the expected margin and the video frame rate drops.

关键词： Automation Accuracy Array signal processing Humanoid robots Oral communication Human factors

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On the Stabilization of a Class of OSL Conformable Fractional Order Nonlinear Systems

On the Stabilization of a Class of OSL Conformable Fractiona...

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International Conference on Systems and control (ICSC)

作者： Ali Omar M. Alsharif A. Jmal O. Naifar Ausama H. Ahmed Hamdi Gassara A. Ben Makhlouf Electrical Engineering Department Control and energy management laboratory (CEM lab) Sfax University Engineering National School Sfax Tunisia Department of Electrical & Computer Engineering Faculty of Engineering Elmergib University Alkhums Libya Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Tunisia Department of Mathematics Faculty of Sciences of Sfax Sfax Tunisia

One-Sided Lipschitz (OSL) fractional order modeling is a top choice for solving the stabilization issue of nonlinear systems. Despite numerous studies on the subject, there remains a gap in understanding when it comes to fractional calculus. By providing a stabilizing strategy for a certain type of OSL fractional order nonlinear systems, this study fills the gap. A numerical example demonstrating the correctness of the suggested approach and demonstrating its efficacy for the tested class.

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Aerial Robots Carrying Flexible Cables: Dynamic Shape Optimal control via Spectral Method Model

arXiv

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arXiv 2024年

作者： Shen, Yaolei Franchi, Antonio Gabellieri, Chiara Faculty University of Twente Enschede7500 AE Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

—In this work, we present a model-based optimal boundary control design for an aerial robotic system composed of a quadrotor carrying a flexible cable. The whole system is modeled by partial differential equations (PDEs) combined with boundary conditions described by ordinary differential equations (ODEs). The proper orthogonal decomposition (POD) method is adopted to project the original infinite-dimensional system on a finite low-dimensional space spanned by orthogonal basis functions. Based on such a reduced order model, nonlinear model predictive control (NMPC) is implemented online to realize both position and shape trajectory tracking of the flexible cable in an optimal predictive fashion. The proposed POD-based reduced modeling and optimal control paradigms are verified in simulation using an accurate high-dimensional FDM-based model and experimentally using a real quadrotor and a cable. The results show the the viability of the POD-based predictive control approach (allowing to close the control loop on the full system state) and its superior performance compared to a optimally tuned PID controller (allowing to close the control loop on the quadrotor state only). © 2024, CC BY.

关键词： Orthogonal functions

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Integrating V2X solutions in intelligent green cities: an AI-driven point exchange system approach

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Neural Computing and Applications 2025年

作者： Talaat, Fatma M. Shaban, Warda M. ZainEldin, Hanaa Badawy, Mahmoud Elhosseini, Mostafa Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt Faculty of Computer Science & Engineering New Mansoura University Gamasa35712 Egypt Department of Communication and Electronics Engineering Nile Higher Institute for Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence and informatics Horus University New Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer Science and Information Department Applied College Taibah University Madinah42353 Saudi Arabia College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia

With rapid urbanization, smart cities have become essential for enhancing urban management and sustainability by integrating technological, social, and institutional innovations. Among these innovations, vehicle-to-everything (V2X) communications and electric vehicles (EVs) play a critical role in reducing carbon emissions and optimizing urban mobility. To address the existing gaps in holistic V2X integration, this paper presents a novel eco-assistive fog-based traffic management system (EAFTMS) that leverages a four-tier architecture (IoT, fog, cloud, and application) for scalable, real-time traffic optimization. A key innovation of this system is the AI-driven point exchange system (PES), designed to incentivize sustainable behaviors such as reducing unnecessary vehicle usage and promoting green lifestyle choices. Unlike conventional models, the proposed framework incorporates real-time behavioral monitoring, rewards-based sustainability programs, and V2X-enabled dynamic traffic control. Empirical validation demonstrates that EAFTMS outperforms existing models, including support vector regression (SVR), achieving a 30% reduction in latency, a 40% improvement in response time, a 25% increase in traffic flow efficiency, and a 35% reduction in CO2 emissions. These results highlight the framework’s potential to set new standards in intelligent green cities by offering scalable, practical, and environmentally impactful solutions to urban transportation challenges. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Urban transportation

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