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Annual Allerton Conference on Communication, control, and Computing

作者： Apostolos I. Rikos Nicolas E. Manitara Gabriele Oliva Christoforos N. Hadjicostis Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA USA Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Engineering Unit of Automatic Control Università Campus Bio-Medico di Roma Rome Italy

In this paper, we enhance a distributed version of the well known k-means algorithm with privacy-preservation features. While ensuring that sensitive or confidential information remains undisclosed to unauthorized entities (in our case these entities are curious nodes within the network), we maintain the desirable features of the distributed algorithm: the transmitted values are quantized, which optimizes bandwidth utilization and alleviates communication bottlenecks, and nodes possess the ability to collectively determine when to terminate the algorithm, which enables the conservation of valuable resources. We introduce a novel privacy-preserving protocol that not only preserves the privacy of a node’s state, but it also ensures confidentiality about its cluster affiliation (i.e., it does not reveal to curious nodes whether a node participates in the update calculation for a specific centroid value). Moreover, we precisely characterize topological conditions that guarantee privacy preservation for individual nodes. Our distributed algorithm allows the formation of exclusive clusters within a finite time frame on any static and strongly connected directed graph.

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Joint State and Parameter Estimation Using the Partial Errors-in-Variables Principle

arXiv

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arXiv 2024年

作者： Liu, Peng Li, Kailai Hendeby, Gustaf Gustafsson, Fredrik Division of Automatic Control Department of Electrical Engineering Linköping University Linköping Sweden Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands

This letter proposes a new method for joint state and parameter estimation in uncertain dynamical systems. We exploit the partial errors-in-variables (PEIV) principle and formulate a regression problem in the sense of weighted total least squares, where the uncertainty in the parameter prior is explicitly considered. Based thereon, the PEIV regression can be solved iteratively through the Kalman smoothing and the regularized least squares for estimating the state and the parameter, respectively. The simulations demonstrate improved accuracy of the proposed method compared to existing approaches, including the joint maximum a posterior-maximum likelihood, the expectation maximisation, and the augmented state extended Kalman smoother. Copyright © 2024, The Authors. All rights reserved.

关键词： Errors

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A Workplace Equality Workshop for the control engineering Classroom

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IFAC-PapersOnLine 2022年第17期55卷 97-102页

作者： Margret Bauer Frida Heskebeck University of Applied Sciences Hamburg Department of Automatic Control Lund University Sweden Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

engineering, in general, is a non-diverse profession around the globe. Women are one group of minorities in engineering. Despite the fact that control engineering is heavily based on mathematics, which has a larger number of female students, it has the same proportion of women as other engineering disciplines. To address the issue of low female participation in engineering disciplines both at university and, more importantly, in career, we have developed a workshop that can be carried out in a 90-minute-lecture in the classroom. In this paper, we first explain the context and need for such a workshop and then present the contents of the developed material as a resource for colleagues in the control engineering community.

关键词： control engineering education diversity inclusion gender equality

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WARA-PS:a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation

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Autonomous Intelligent Systems 2021年第1期1卷 104-134页

作者： Olov Andersson Patrick Doherty Mårten Lager Jens-Olof Lindh Linnea Persson Elin A.Topp Jesper Tordenlid Bo Wahlberg Department of Computer and Information Science Linköping UniversityLinköpingSweden Saab Kockums MalmöSweden Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of TechnologyStockholmSweden Department of Computer Science Lund UniversityLundSweden Saab Combitech AB LinköpingSweden Division of Automatic Control Department of Electrical EngineeringLinköping UniversityLinköpingSweden

A research arena(WARA-PS)for sensing,data fusion,user interaction,planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is *** objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal *** enabler is a computational infrastructure with a core system architecture for industrial and academic *** includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial *** motivating application for the demonstration is marine search and rescue operations.A state-of-art delegation framework for the mission planning together with three specific applications is also *** first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface *** second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles,and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine *** research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test *** would be most difficult to do experiments on this large scale without the WARA-PS research ***,these demonstrator activities have resulted in effective research dissemination with high public visibility,business impact and new research collaborations between academia and industry.

关键词： Autonomous systems Intelligent system architectures Research demonstration arena Autonomous drones Autonomous marine vessels Public safety and security Collaborative robotics

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Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers

Biological Influence of Low-Frequency Electromagnetic Field ...

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ELEKTRO

作者： Robert Cichorowski Olga Kocikowska Marek Bajtoš Roman Radil Ladislav Janoušek Daria Gendosz De Carrillo Sebastian Student Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology liwice Poland Department of Engineering and Systems Biology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Department of Physiology Faculty of Medical Sciences Silesian University of Medicine Katowice Poland Department of Electromagnetic and Biomedical Engineering Faculty of Electrical Engineering and Informational Technology Žilina Slovakia Department of Histology Faculty of Medical Sciences in Zabrze Silesian University of Medicine Zabrze Poland Biotechnology Center Silesian University of Technology Gliwice Poland

ISBN: (数字)9798350372359

ISBN: (纸本)9798350372366

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week.

关键词： Proteins Biological system modeling Estimation Electromagnetic fields

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automatic Detection of Lumbar Disc Herniation Using YOLOv7

Automatic Detection of Lumbar Disc Herniation Using YOLOv7

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Prisilla, Ardha Ardea Pusparani, Yori Chang, Wen-Thong Liau, Ben-Yi Jan, Yih-Kuen Ardhianto, Peter Lin, Chih-Yang Lung, Chi-Wen Asia University Taichung Department of Digital Media Design Taiwan LaSalle College Jakarta Department of Fashion Design Jakarta Indonesia Budi Luhur University Department of Visual Communication Design Jakarta Indonesia Department of Computer Science and Information Engineering Taichung Taiwan Feng Chia University Department of Automatic Control Engineering Taichung Taiwan Asia University Department of Creative Product Design Taichung Taiwan Soegijapranata Catholic University Department of Visual Communication Design Semarang Indonesia National Central University Department of Mechanical Engineering Taoyuan Taiwan

ISBN: (纸本)9798350324174

The detection of lumbar disc herniation (LDH) through magnetic resonance imaging (MRI) poses a challenge due to the various shapes, sizes, angles, and regions associated with bulges, protrusions, extrusions, and sequestrations. One potential solution is using deep learning methods to identify lumbar abnormalities in MRI images automatically. The YOU ONLY LOOK ONCE (YOLO) model series has gained popularity for training deep learning algorithms for real-time biomedical image detection. This study aims to assess the performance of the latest YOLOv7 in detecting LDH across different regions of the lumbar intervertebral disc. The analysis revealed that YOLOv7 exhibits a poor performance and low detection rate of LDH across the L1-L2, L2-L3, L3-L4, L4-L5, and L5-S1 regions. © 2023 IEEE.

关键词： Magnetic resonance imaging

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A Hybrid Temporal-Magnitude Based Sampling for Event-Based control

A Hybrid Temporal-Magnitude Based Sampling for Event-Based C...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Oscar Miguel-Escrig José Sánchez-Moreno Julio-Ariel Romero-Pérez Sebastián Dormido-Bencomo Department of System Engineering and Design Universitat Jaume I Castelló de la Plana Spain Department of Computer Science and Automatic Control Universidad Nacional de Educación a Distancia (UNED) Madrid Spain

ISBN: (数字)9798331540319

ISBN: (纸本)9798331540326

In the current industrial environment, which is shifting towards an event-based control prone paradigm, sampling strategies in use must be revisited. Both temporal and magnitude dependent sampling strategies have been demonstrated to be suitable for control systems, reporting benefits in different categories. However, these sampling strategies also present some drawbacks, discussed in this contribution. Aiming to address some of these drawbacks, a new sampling strategy is proposed gathering characteristics of both predecessors.

关键词： Industrial electronics Transient response Quantization (signal) Event detection control systems Hybrid power systems Steady-state Data communication Guidelines

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H control for General Conformable Polynomial Fuzzy Models

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International Journal of Fuzzy Systems 2025年 1-10页

作者： Laajimi, Malek Gassara, Hamdi Rhaima, Mohamed Mchiri, Lassaad Makhlouf, Abdellatif Ben Laboratory of Sciences and Techniques of Automatic control & Computer Engineering National School of Engineering of Sfax Sfax Tunisia Department of Statistics and Operations Research College of Science King Saud University Riyadh Saudi Arabia Panthéon-Assas University Paris II Paris France Department of Mathematics Faculty of Sciences Sfax University Sfax Tunisia

This research focuses on exploring the exponential $$H_\infty $$ stability of general conformable nonlinear system. In order to address the nonlinearity inherent in the system, a polynomial fuzzy (PF) method is employed. Modeling a general conformable nonlinear system within the polynomial framework reduces the number of fuzzy rules compared to the classical Takagi–Sugeno fuzzy (TSF). Furthermore, controlling such a complex system, which accounts for perturbations, employs a PF model instead TSF model to describe its nonlinear dynamics, and incorporates a general conformable derivative instead of an integer-order one, is significantly more challenging, and remains unaddressed in previous studies. In this paper, a PF controller is designed in the form of sum of squares (SOS) to enhance the resilience against perturbations and ensure the exponential stability of the proposed model. The proposed SOS can be solved numerically, and partially symbolically, using the recently developed SOSTOOLS. In order to ensure the $$H_\infty $$ performance, a generalized criterion is defined for the general conformable nonlinear system. To demonstrate the effectiveness of the proposed method, a numerical example is provided.

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Enhancing Wastewater Treatment Sensor Fault Detection through Deep Learning

Enhancing Wastewater Treatment Sensor Fault Detection throug...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Liliana-Maria Ghinea Mihaela Miron Marian Barbu Department of Automatic Control and Electrical Engineering University "Dunărea de Jos" Galați Romania Department of Computer Science and Information Technology University "Dunărea de Jos" Galați Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

Efficient operation and maintenance of wastewater treatment plants (WWTPs) are essential for safeguarding public health and the environment. The emergence of mechanical faults within complex systems can lead to disruptions, increased operational costs, and environmental risks. As the world moves towards a digitally connected and sustainable future, the development of Deep Learning (DL) tools for fault detection and isolation (FDI) in wastewater treatment processes is expected to become paramount. Therefore, in this study, we developed two neural models, a Feedforward Neural Network (FFNN) and a Long Short-Term Memory (LSTM), to address the detection of mechanical faults such as bias, stuck, spikes, and precision degradation of the Dissolved Oxygen (DO) sensor. The classification results showed remarkable accuracy performances during testing: for Dataset 1, FFNN achieved 96.56%, while LSTM reached 99.36%; and for Dataset 2, FFNN achieved 99.36%, and LSTM reached 99.57%.

关键词： Deep learning Degradation Accuracy Fault detection Plants (biology) Biological system modeling Data models Wastewater treatment Long short term memory Testing

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Error Dependent Sampling to Reduce Transient Events in Event Based control

Error Dependent Sampling to Reduce Transient Events in Event...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Oscar Miguel-Escrig Julio-Ariel Romero-Pérez José Sánchez-Moreno Sebastián Dormido-Bencomo Department of System Engineering and Design Universitat Jaume I Castelló de la Plana Spain Department of Computer Science and Automatic Control Universidad Nacional de Educación a Distancia (UNED) Madrid Spain

ISBN: (数字)9798331540319

ISBN: (纸本)9798331540326

One of the objectives of event-based control is the reduction of generated events to perform an appropriate process control. Among the event generation techniques used to this end, those quantifying the error signal can be found more frequently for its simplicity of implementation. However, they entail a drawback in the form of trade-off between event generation and performance. Aiming to reduce the number of events, specifically in the transient response, without degrading the performance, an error dependent sampling scheme is studied in this work.

关键词： Industrial electronics Transient response Event detection Process control Robustness Regulation Generators Transient analysis

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