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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2023年第3期85卷 37-48页

作者： Riciu, Ionela Dobrescu, Radu Faculty of Automatic Control and Computers Systems Engineering University of Bucharest Romania Systems Engineering field Faculty of Automatic Control and Computers University of Bucharest Romania

This paper highlights the relationship between the notions of meaning and respectively the semantic notion of qualia as they appear in cybersemiotic models of information transmission. The research work proposes a new way to model the perception of meaning in brain, based on an original cybernetic aproach of the relation between information structures and information messages at the level of brain’s neuronal networks. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Semantics

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A NOTE ON THE QUALITATIVE BEHAVIOUR OF AN ODE MODEL RELATED TO ENDOTOXIN TOLERANCE

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2024年第4期86卷 127-130页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

关键词： Differential equations

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The Unscented Kalman Filter for Nonlinear Parameter Identification of Adaptive Cruise control systems

arXiv

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arXiv 2023年第8期8卷 4094页

作者： Ampountolas, Konstantinos The Automatic Control & Autonomous Systems Laboratory Department of Mechanical Engineering University of Thessaly Volos38334 Greece

This paper develops and investigates a dual unscented Kalman filter (DUKF) for the joint nonlinear state and parameter identification of commercial adaptive cruise control (ACC) systems. Although the core functionality of stock ACC systems, including their proprietary control logic and parameters, is not publicly available, this work considers a car-following scenario with a human-driven vehicle (leader) and an ACC engaged ego vehicle (follower) that employs a constant timeheadway policy (CTHP). The objective of the DUKF is to determine the CTHP parameters of the ACC by using real-time observations of space-gap and relative velocity from the vehicle's onboard sensors. Real-time parameter identification of stock ACC systems is essential for assessing their string stability, large-scale deployment on motorways, and impact on traffic flow and throughput. In this regard, L2and L∞string stability conditions are considered. The observability rank condition for nonlinear systems is adopted to evaluate the ability of the proposed estimation scheme to estimate stock ACC system parameters using empirical data. The proposed filter is evaluated using empirical data collected from the onboard sensors of two 2019 SUV vehicles, namely Hyundai Nexo and SsangYong Rexton, equipped with stock ACC systems;and is compared with batch and recursive least-squares optimization. The set of ACC model parameters obtained from the proposed filter revealed that the commercially implemented ACC system of the considered vehicle (Hyundai Nexo) is neither L2nor L∞string stable. Copyright © 2023, The Authors. All rights reserved.

关键词： Adaptive cruise control

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A Power-Communication Co-Simulation Platform for Real-Time Microgrid Cyber Security Analysis

A Power-Communication Co-Simulation Platform for Real-Time M...

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2024 International Conference on Artificial Intelligence of Things and systems, AIoTSys 2024

作者： Qiu, Dongmeng Liu, Mengxiang Zhang, Xin University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798331507886

The rapid digitalisation process in power system has greatly benefited the large-scale integration of distributed energy resources (DERs), essentially accelerating the progress towards net zero. However, numerous cyber attacks such as false data injection (FDI) attacks are impeding the normal control and operation activities. This paper aims to establish a real-Time microgrid co-simulation platform to fully study the impacts of realistic attack events on micorgrid's control performance. Although there exist a large number of power-communication co-simulation platforms for the power system, they are designed to mainly provide validation services for control and operation algorithms and little attention has been paid to the cyber security. In the established microgrid platform, power and communication parts are simulated in Typhoon Hardware-in-The-loop(HIL) 602+ and EXata Network Simulator, respectively, and a dedicated synchronisation scheme is developed and embedded in Raspberry Pis to achieve master-slave data exchange between them. Based on the advanced cyber libraries provided by EXata, realistic FDI and packet drop attacks are mounted against the mapped communication links within EXata. The results indicate that these cyber attacks can severely influence the microgrid control performance including destabilising system states and specific state deviations, further demonstrating the necessity of deploying effective cyber-resilience enhancement mechanisms. © 2024 IEEE.

关键词： Cyber attacks

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Learning Input Driven Dynamic Bayesian Networks with Measurement Noise 23

Learning Input Driven Dynamic Bayesian Networks with Measure...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Veres, David Li, Ping Kadirkamanathan, Visakan The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350374889

Dynamic Bayesian Networks (DBNs) are useful tools for modelling complex systems whose network representations can be elicited a priori or learnt from data. In this paper, a maximum likelihood Doubly-Iterative Expectation Maximization (DI-EM) Algorithm is developed for the identification of grey-box ARMAX state-space model representations of DBNs involving known, noisy measurement processes. The grey-box model incorporates network dependencies among time series variables and exploits time series data of low longitudinal and high cross-sectional dimensions. A network learning procedure is developed using a score-based structure-selection method to find the underlying network of an input-driven dynamical system. By computing a finite data version of the Bayesian Information Criterion (BIC) for small sample sizes, the proposed method's performance is investigated on simulated and real-world data. The algorithm recovers the underlying ground-truth networks of simulated systems under finite data criteria with Jaccard Coefficient values of up to 0.84, and selects structures with improved weighted mean-squared error loss over a baseline black-box model fit on real-world data. © 2024 IEEE.

关键词： Expectation maximization algorithm

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Optimized Spatial Filter Selection for Transfer Learning in Brain-Computer Interface 3

Optimized Spatial Filter Selection for Transfer Learning in ...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： A A Mohamed, Mohamed Giles, Joshua Arvaneh, Mahnaz University of Sheffield Automatic control and Systems Engineering Department Sheffield United Kingdom

ISBN: (纸本)9798350378009

The Common Spatial Patterns (CSP) algorithm has shown great efficacy in extracting features for Brain-Computer Interfaces (BCIs), particularly in motor imagery BCIs. However, CSP performs poorly when dealing with limited labeled data, which leads to long calibration time at the beginning of each session. To overcome this challenge, we leverage source data, i.e., labeled data from other subjects, to transfer knowledge across subjects. This work proposes a novel approach termed Scaled and Warped CSP-based Transfer Learning (SW-CSP-TL). This method aligns source data with the temporal and amplitude structure of target data before computing CSP filters, ensuring optimization for capturing discriminative features relevant to the target domain. We evaluate the proposed SW-CSP-TL algorithm using the publicly available dataset 2a from BCI Competition IV and compare its performance with that of the classical CSP algorithm and the transfer learning CSP algorithm (CSP-TL) without amplitude scaling and temporal warping. Our algorithm exhibits superior performance particularly when the training data size is relatively small. Results demonstrate that for 5 and 15 training trials per class from the target session, SW-CSP-TL outperformed the classical CSP by an average of 10%, and 8%, respectively. © 2024 IEEE.

关键词： Transfer learning

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Distributed Consensus control of Nonlinear Multiagent systems With Output Noises Via a Switching Classification Approach

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IEEE Transactions on automatic control 2025年第6期70卷 4132-4139页

作者： Li, Kuo Ding, Steven X. Hua, Changchun Li, Yafeng Yang, Yana Yanshan University School of Electrical Engineering Qinhuangdao066004 China University of Duisburg-Essen Institute for Automatic Control and Complex Systems Duisburg47057 Germany

This paper explores the distributed leader-following consensus control problem of nonlinear multiagent systems subject to stochastic output sensing noises under a fixed directed topology. Different from existing research, we pay attention to the effect of multiplicative stochastic noises on the sensors, and the noise intensity can be described as an unknown time-varying function with an arbitrarily large bound. In this condition, we put forward the noise intensity classification-based distributed output feedback consensus approach. First, we divide the noise intensity into small-noise intensity and large-noise intensity by designing a demarcation constant, and we introduce the switching property to distinguish them. Then, for the follower, we design the distributed controller based on the established compensator utilizing relevant outputs, and we produce sufficient conditions for the controller to be implemented. Subsequently, a unified Lyapunov function is constructed to prove that all agents can realize the full-state exponential consensus in mean square under the action of the controller. Finally, the simulation example is provided to demonstrate the efficiency of our approach. © 1963-2012 IEEE.

关键词： Lyapunov functions

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A Lightweight Target Following Architecture for Indoor Mobile Robot 25

A Lightweight Target Following Architecture for Indoor Mobil...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Wang, Fuli Hutabarat, Windo Tiwari, Ashutosh The University Of Sheffield Department Of Automatic Control And Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340266

Manufacturing efficiency and transport operations are being significantly improved by mobile robots. As the implementation of a configurable, lightweight, and stateof-the-art robotic system is required for current manufacturing sectors to maximize the use of mobile robots, this paper presents a software architecture comprised of perception and action systems for human following in real time. The perception system uses the YOLOv8 computer vision model to identify and estimate human pose. Additionally, an algorithm is developed using the 3D information from a stereo camera to determine which target and whether to follow. Once the perception system perceives the desired target information, the action system can control and coordinate the robot using the ROS. Experimental results from the physical robot demonstrate the feasibility of the system architecture. © 2024 IEEE.

关键词： Mobile robots

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A MATHEMATICAL MODEL ILLUSTRATING THE INHIBITORY EFFECT OF THE MICRO RNA ON THE PROTEIN PRODUCTION

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2023年第4期85卷 101-106页

The present paper introduces a mathematical model for the cross-talking between microRNA and Protein. Studying the qualitative properties of the proposed model, we infer that the microRNA is an inhibitor for the Prote... 详细信息

关键词： Proteins

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Pneumonia Detection from X-ray Images Using Convolutional Neural Networks 24

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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24th International Conference on control systems and Computer Science, CSCS 2023

作者： Dediu, Viorel Udrea, Andreea Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia. © 2023 IEEE.

关键词： Convolution

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