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Model-based Dependability Analysis of Fault-tolerant Inertial Navigation System: A Practical Experience Report

IFAC-PapersOnLine 2019年第12期52卷 394-399页

作者： Mikael Steurer Andrey Morozov Klaus Janschek Klaus-Peter Neitzke Faculty of Electrical Engineering Automatic Control and Informatics Institute of Computer Science Opole University of Technology Poland

Model-based systems engineering approaches are commonly used to develop safetycritical mechatronic systems. Recently, a new SysML-based method for the dependability analysis of Unmanned Aerial Vehicles (UAVs) has been introduced. The method consists of three main steps: (i) creation of a structural SysML model using building blocks from the underlying UAV dependability profile that extends the model with block-level reliability and time properties, (ii) transformation of the semi-formal SysML model into a formal Dual-Graph Error Propagation Model (DEPM) that captures relevant structural and behavioral properties of the system, (iii) DEPM-based evaluation of system dependability metrics using Markov chain models and state-of-the-art probabilistic model checking techniques. This paper describes the practitioner experiences and lessons learned after the application of the aforementioned method to a sophisticated real-world embedded fault-tolerant inertial navigation system. The case study revealed two particular limitations that have been overcome by the optimization of the method against the state-space explosion of underlying Markov chain models and the introduction of a new computation algorithm for DEPMs with realistic extremely low fault activation probabilities.

关键词： system analysis design systems architecture reliability engineering dependability SysML Markov chains microsensors space technology

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Network Realization Functions for Optimal Distributed control

arXiv

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arXiv 2021年

作者： Sabau, Şerban Sperila, Andrei Oara, Cristian Jadbabaie, Ali Electrical and Computer Engineering Department Stevens Institute of Technology HobokenNJ07030 United States Faculty of Automatic Control and Computers "Politehnica" University of Bucharest Sector 6 060042 Romania CambridgeMA02139 United States

In this paper, we discuss a distributed control architecture, aimed at networks with linear and time-invariant dynamics, which is amenable to convex formulations for controller design. The proposed approach is well suited for large scale systems, since the resulting feedback schemes completely avoid the exchange of internal states, i.e., plant or controller states, among sub-controllers. Additionally, we provide state-space formulas for these sub-controllers, able to be implemented in a distributed manner. © 2021, CC BY.

关键词： Large scale systems

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Integrated Learning in electrical and control engineering Using an Educational Elevator System

Integrated Learning in Electrical and Control Engineering Us...

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International Conference and Exposition on electrical and Power engineering (EPE)

作者： Dorin-Dumitru Lucache Georgel Gabor Constantin-Cătălin Dosoftei Faculty of Electrical Eng. Energy and Applied Informatics “Gheorghe Asachi” Technical University of Iasi Iasi Romania Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9781728181264

ISBN: (纸本)9781728181271

The research of the authors is focused on presenting a practical multidisciplinary experiment - an elevator simulator to relate theory and practice inside of a lot of disciplines and to bring the “real world” into a useful case study for electrical and control engineering education. Through the existence of interesting experiments, students gain motivation either to continue thinking and improving new solutions for building and control of elevators. The concept of the modern elevator is presented in this paper from the perspective of integration of current technological equipment like a programmable logic controller, inverter, encoder, human-machine-interface on which students can develop various control strategies using a SCADA system. The paper presents the some exercises that students can perform on the existent simulator.

关键词： Elevators Registers Induction motors Software Coils Traction motors Inverters

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Parametric activation functions modelling fuzzy connectives for better explainability of neural models

Parametric activation functions modelling fuzzy connectives ...

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International Symposium on Intelligent Systems and informatics (SISY)

作者： Luca Sára Pusztaházi Gábor Csiszár Michael S. Gashler Orsolya Csiszár Physiological Control Research Center Obuda University Budapest Hungary Applied Informatics and Applied Mathematics Doctoral School Obuda University Budapest Hungary Physiological Control Research Center Obuda University Budapest Hungary Institute of Materials Physics University of Stuttgart Stuttgart Germany SupplyPike Fayetteville Arkansas USA Physiological Control Research Center Hungary Faculty of Electrical Engineering and Computer Science Obuda University Budapest Aalen University Aalen Germany

ISBN: (纸本)9781665489898

In this work, a neuro-fuzzy hybrid deep learning model is presented for finding human-readable relationships between input features with the help of nilpotent fuzzy logic and multi-criteria decision making (MCDM). In the neural network a parameterized, differentiable activation function is used, where the parameter is determined by gradient descent. The goal is to find the optimal regularization value by applying the deep learning model to classification problems from the UCI Machine Learning Repository.

关键词： Deep learning Fuzzy logic Neural networks Decision making Intelligent systems informatics Tuning

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Empirical evaluation of continuous test-driven development in industrial settings

Empirical evaluation of continuous test-driven development i...

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作者： Madeyski, Lech Kawalerowicz, Marcin Faculty of Computer Science and Management Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50-370 Poland Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

BACKGROUND: Continuous Test-Driven Development (CTDD) is, proposed by the authors, enhancement of the well-established Test-Driven Development (TDD) agile software development and design practice. CTDD combines TDD with continuous testing (CT) that essentially perform background testing. The idea is to eliminate the need to execute tests manually by a TDD-inspired developer. OBJECTIVE: The objective is to compare the efficiency of CTDD vs TDD measured by the red-to-green time (RTG time), i.e., time from the moment when the project is rendered not compiling or any of the tests is failing, up until the moment when the project compiles and all the tests are passing. We consider the RTG time to be a possible measurement of efficiency because the shorter the RTG time, the quicker the developer is advancing to the next phase of the TDD cycle. METHOD: We perform single case and small-n experiments in industrial settings presenting how our idea of Agile Experimentation materialise in practice. We analyse professional developers in a real-world software development project employing ***. We extend the contribution presented in our earlier paper by: 1) performing additional experimental evaluation of CTDD and thus collecting additional empirical evidence, 2) giving an extended, detailed example how to use and analyse both a single case and small-n experimental designs to evaluate a new practice (CTDD) in industrial settings taking into account natural constraints one may observe (e.g., a limited number of developers available for research purposes) and presenting how to reach more reliable conclusions using effect size measures, especially PEM and PAND which are more appropriate when data are not normally distributed or there is a large variation between or within phases. RESULTS: We observed reduced variance and trimmed means of the RTG time in CTDD in comparison to TDD. Various effect size measures (including ES, d-index, PEM, and PAND) indicate small, albeit non-

关键词： Software design

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A Review of Neuro-ML Breakthroughs in Addressing Neurological Disorders

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Applied Sciences 2025年第10期15卷 5442-5442页

作者： Cosmina-Mihaela Rosca Adrian Stancu Department of Automatic Control Computers and Electronics Faculty of Mechanical and Electrical Engineering Petroleum-Gas University of Ploiesti 39 Bucharest Avenue 100680 Ploiesti Romania Department of Business Administration Faculty of Economic Sciences Petroleum-Gas University of Ploiesti 39 Bucharest Avenue 100680 Ploiesti Romania

This research aims to explore the interdisciplinary connection between the field of neurology and artificial intelligence (AI) through machine learning (ML) algorithms. The central objective is to evaluate the current state of research in the Neuro-ML field and identify gaps in the literature that require additional approaches. To achieve this objective, 10 analyses were introduced that analyze the distribution of articles based on keywords, countries, years, publishers, and ML algorithms used in the context of neurological diseases. Surveys were also conducted to identify the diseases most frequently studied through ML algorithms. Thus, it was found that Alzheimer’s disease (37 articles for Support Vector Regression—SVR; 31 for Random Forest—RF), Parkinson’s disease (46 articles for SVM and 48 for RF), and multiple sclerosis (9 articles for SVM) are the most studied diseases in the field of Neuro-ML. The study analyzes Alzheimer’s, Parkinson’s, and multiple sclerosis in detail by focusing on diagnosis. The overall results highlight an increase in researchers’ interest in applying ML in neurology, with models such as SVM (597 articles), Artificial Neural Network (525 articles), and RF (457 articles) being the most used. The results highlighted three major gaps: the underrepresentation of rare diseases, the lack of standardization in evaluating the performance of ML models, and the lack of exploration of algorithms with greater implementation difficulty, such as Extreme Gradient Boosting and Multilayer Perceptron. The value analysis of the performance metrics of ML models demonstrates the ability to correctly classify neuro-degenerative diseases, with high accuracy in some cases (for example, 97.46% accuracy in Alzheimer’s diagnosis), but there may still be improvements. Future directions include exploring rare diseases, investigating underutilized algorithms, and developing standardized protocols for evaluating the performance of ML models, which will facilitate the

关键词： artificial intelligence machine learning Alzheimer’s and Parkinson’s diseases amyotrophic lateral sclerosis frontotemporal dementia Huntington’s disease Lewy body dementia Creutzfeldt–Jakob disease spinocerebellar ataxia multiple sclerosis

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An analytical drain current model for dual-material gate graded-channel and dual-oxide thickness cylindrical gate (DMG-GC-DOT) MOSFET

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Nanoscience and Nanotechnology - Asia 2019年第2期9卷 291-297页

作者： Jaafar, Hind Aouaj, Abdellah Bouziane, Ahmed Iñiguez, Benjamin Faculty of Science and Technology Laboratory of Automatic Conversion of Energy and Microelectronics University Sultan Moulay Slimane Beni Mellal Morocco Department of Electronic Electrical and Automatic Control Engineering Universitat Rovira i Virgili Av Paisos Catalans 26 Tarragona43007 Spain

Background: A novel Dual Material Gate Graded Channel and Dual Oxide Thickness Cylindrical Gate (DMG-GC-DOT) MOSFET is presented in this paper. Methods: Analytical model of drain current is developed using a quasi-two-dimensional cylindrical form of the Poisson equation and is expressed as a function of the surface potential, which is calculated using the expressions of the current density. Results: Comparison of the analytical results with 3D numerical simulations using Silvaco Atlas-TCAD software presents a good agreement from subthreshold to strong inversion regime and for different bias voltages. Conclusion: Two oxide thicknesses with different permittivity can effectively improve the subthreshold current of DMG-GC-DOT MOSFET. © 2019 Bentham Science Publishers.

关键词： Drain current

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2D nanomaterials for realization of flexible and wearable gas sensors: A review

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Chemosphere 2024年 352卷 141234页

作者： Pawar, Krishna Kiran Kumar, Ashok Mirzaei, Ali Kumar, Mahesh Kim, Hyoun Woo Kim, Sang Sub Division of Materials Science and Engineering Hanyang University Seoul 04763 South Korea The Research Institute of Industrial Science Hanyang University Seoul 04763 South Korea School of Nanoscience and Technology Shivaji University Kolhapur 416004 India Department of Electrical Engineering Indian Institute of Technology Jodhpur 342030 India Department of Materials Science and Engineering Shiraz University of Technology Shiraz 715557-13876 Iran Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice 44-100 Poland Department of Materials Science and Engineering Inha University Incheon 22212 South Korea

Gas sensors are extensively employed for monitoring and detection of hazardous gases and vapors. Many of them are produced on rigid substrates, but flexible and wearable gas sensors are needed for intriguing usage including the internet of things (IoT) and medical devices. The materials with the greatest potential for the fabrication of flexible and wearable gas sensing devices are two-dimensional (2D) semiconducting nanomaterials, which consist of graphene and its substitutes, transition metal dichalcogenides, and MXenes. These types of materials have good mechanical flexibility, high charge carrier mobility, a large area of surface, an abundance of defects and dangling bonds, and, in certain instances adequate transparency and ease of synthesis. In this review, we have addressed the different 2D nonmaterial properties for gas sensing in the context of fabrication of flexible/wearable gas sensors. We have discussed the sensing performance of flexible/wearable gas sensors in various forms such as pristine, composite and noble metal decorated. We believe that content of this review paper is greatly useful for the researchers working in the research area of fabrication of flexible/wearable gas sensors. © 2024 Elsevier Ltd

关键词： 2D nanomaterials Flexible/wearable gas sensor Graphene MXenes Sensing mechanism TMDs Toxic gas

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The Energy Efficiency of a Prosumer in a Photovoltaic System

The Energy Efficiency of a Prosumer in a Photovoltaic System

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International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Marius-Alexandru Dobrea Stefan Bichiu Ioana Opris Mihaela Vasluianu Faculty of Automatic Control and Computer Science UPB Bucharest Romania Faculty of Power Engineering UPB Bucharest Romania Collective of Automation and Applied Informatics Faculty of Hidrotehnics UTCB Bucharest Romania

ISBN: (数字)9781728175065

ISBN: (纸本)9781728175072

This article aims to calculate the net income achieved by a prosumer for an existing On-Grid system of photovoltaic panels consisting of a set of 12 poly crystalline panels with a nominal power of 250 Wand 60 cells and an On-Grid inverter (StecaGrid model) with a maximum power of 3000 W. The prosumer is located in southern Romania, Ilfov County. Modeling of the photovoltaic panel in Matlab / SIMULINK was performed using a mathematical model, and it was compared with a real data set. Next, an analysis was made of the energy produced by the photovoltaic system, and the energy consumed by the prosumer, the excess energy being introduced in the national energy system. We have achieved a net income saving for March, so the analyzed photovoltaic system has energy efficiency that can significantly reduce electricity costs over time. Thus, using the Matlab / Simulink model, photovoltaic systems can be designed to satisfy the needs of prosumers.

关键词： Photovoltaic systems Mathematical model Solar power generation Software packages Inverters Temperature Temperature measurement

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Design of Automotive HMI: New Challenges in Enhancing User Experience, Safety, and Security

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Applied Sciences 2025年第10期15卷 5572-5572页

作者： Iwona Grobelna David Mailland Mikołaj Horwat Institute of Automatic Control Electronics and Electrical Engineering University of Zielona Góra 65-516 Zielona Góra Poland Independent Researcher 31000 Toulouse France Faculty of Engineering and Technical Sciences University of Zielona Góra 65-516 Zielona Góra Poland

Human–Machine Interfaces (HMIs) in traditional automobiles are essential in connecting drivers, passengers, and vehicle systems. In automated vehicles, the HMI has become a critical component. A well-designed HMI facilitates effective human oversight, enhances situational awareness, and mitigates risks associated with system failures or unexpected scenarios. Simultaneously, it serves as a crucial safeguard against cyber threats, preventing unauthorized access and ensuring the integrity of vehicular operations in increasingly connected environments. This narrative review delves into the evolving landscape of automotive HMI design, emphasizing its role in enhancing user experience (UX) and safety. By exploring usability challenges, technological advancements, and the integration of rapidly evolving technologies such as AI (Artificial Intelligence), AR (Augmented Reality), and gesture-based controls, this study highlights how effective HMIs minimize cognitive load while maintaining functionality. Significant attention is given to the new challenges that arise from technological advancements in terms of security and safety.

关键词： automotive human–machine interfaces automotive interfaces automotive design vehicle safety user experience

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