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63rd IEEE Conference on Decision and control, CDC 2024

作者： Stenger, David Scheurenberg, Dominik Vallery, Heike Trimpe, Sebastian Institute for Data Science in Mechanical Engineering Rwth Aachen University Germany Institute of Automatic Control Rwth Aachen University Germany Delft University of Technology Department of BioMechanical Engineering Department for Rehabilitation Medicine Erasmus MC Rotterdam Netherlands

ISBN: (纸本)9798350316339

Manual tuning of performance-critical controller parameters can be tedious and sub-optimal. Bayesian Optimization (BO) is an increasingly popular practical alternative to automatically optimize controller parameters from few experiments. Standard BO practice is to evaluate the closed-loop performance of parameters proposed during optimization on an episode with a fixed length. However, fixed-length episodes can be wasteful. For example, continuing an episode where already the start shows undesirable behavior such as strong oscillations seems pointless. Therefore, we propose a BO method that stops an episode early if suboptimality becomes apparent before an episode is completed. Such early stopping results in partial observations of the controller's performance, which cannot directly be included in standard BO. We propose three heuristics to facilitate partially observed episodes in BO. Through five numerical and one hardware experiment, we demonstrate that early stopping BO can substantially reduce the time needed for optimization. © 2024 IEEE.

关键词： Proportional control systems

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Synthesis of Variable Gain Robust State Observer for a Class of Uncertain Nonlinear Systems 6

Synthesis of Variable Gain Robust State Observer for a Class...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Hirasawa, Kazuhiro Asada, Daiki Nagai, Shunya Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798350380040

This paper proposes a new variable gain robust state observer for a class of uncertain nonlinear systems. The variable gain robust state observer proposed in this paper consists of fixed observer gain matrices and nonlinear modification functions which are determined by appropriate updating rules. It is shown that sufficient conditions for the existence of the proposed variable gain robust state observer can be reduced to solvability of Linear Matrix Inequalities (LMIs). Finally, we give a simple numerical example. © 2024 IEEE.

关键词： State estimation

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Some Remarks on Fault-Tolerant Dynamic control Allocation for Weakly Redundant Systems 32

Some Remarks on Fault-Tolerant Dynamic Control Allocation fo...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Cristofaro, Andrea Faleschini, Michelangelo Sapienza University of Rome Department of Computer Control and Management Engineering Italy School of Science and Technology Mathematics Division University of Camerino Italy

ISBN: (纸本)9798350395440

We consider the problem of control allocation for weakly redundant systems subject to actuator faults. In particular, the design of a suitable allocator will be devised with the aim of compensating for the fault effects while, at the same time, keeping the control burden as low as possible. To this goal, two approaches can be followed for the synthesis of the allocation servomechanism: direct allocation using orthogonal projection and optimization-based allocation. Some numerical examples illustrate and highlight advantages, disadvantages and limitations of both strategies. © 2024 IEEE.

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A Robust Guaranteed Cost Formation control for a Class of Uncertain Multi-Agent Systems for Event-Trigger-Based Variable Gain controllers 6

A Robust Guaranteed Cost Formation Control for a Class of Un...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Asada, Daiki Oya, Hidetoshi Nagai, Shunya Hoshi, Yoshikatsu Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan

ISBN: (纸本)9798350380040

In this paper, we propose a design method for a new event-trigger-based variable gain robust controller which achieves both consensus and guaranteed cost performance for a class of uncertain multi-agent systems (MASs) with the leader-follower structure. The proposed variable gain robust controller is composed of stabilizing state feedback laws, state feedback inputs for consensus, and compensation inputs with adjustable parameters, and is designed for giving consideration to relative positions explicitly. In this paper, we show that sufficient conditions for the existence of the proposed robust guaranteed cost formation controller are given in terms of Linear Matrix Inequalities (LMIs). Finally, a simple example is included. © 2024 IEEE.

关键词： State feedback

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Analysis of CNN and Feed-Forward ANN Model for the Evaluation of ECG Signal

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Current Signal Transduction Therapy 2023年第1期18卷 1-8页

作者： Mathur, Prerak Sharma, Tanu Veer, Karan Department of Instrumentation and Control Engineering Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar India

Background: Heart disease is considered one of the complex diseases that has affected a large number of people around the world. It is important to detect and identify cardiac diseases at early stages. Objective: A large number of methods are already present that detect various heart diseases;how-ever, there are some limitations to these methods, that have degraded their overall performance. Methods: In this paper, an effective and efficient method based on a convolutional neural network (CNN) and a feed-forward artificial neural network (FFANN) is proposed that can effectively detect cardiac diseases after analysing the electrocardiogram (ECG) signals. In this ongoing study, the transformed signals are used to extract the information from the processed data. The extracted features are then passed to the proposed CNN-FFANN classifiers for training and testing purposes. Results: The performance of the proposed CNN-FFANN model is evaluated in the MATLAB software in terms of performance matrices. Conclusion: The simulated outcomes have proved the proposed CNN-FFANN model to be more accurate and efficient in detecting heart diseases from ECG signals and can be adopted for future biomedical applications. © 2023 Bentham science Publishers.

关键词： artificial intelligence artificial neural network biomedical applications cardiac diseases ECG signal health monitoring system

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Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

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computers, Materials & Continua 2023年第1期74卷 801-815页

作者： Yongjie Yang Shanshan Tu Raja Hashim Ali Hisham Alasmary Muhammad Waqas Muhammad Nouman Amjad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Information Security and Cybersecurity Unit King Khalid UniversityAbhaSaudi Arabia Computer Engineering Department College of Information TechnologyUniversity of Bahrain32038Bahrain School of Engineering Edith Cowan UniversityJoondalup PerthWA6027Australia School of Engineering University of Management and TechnologyLahorePakistan

With the recent developments in the Internet of Things(IoT),the amount of data collected has expanded tremendously,resulting in a higher demand for data storage,computational capacity,and real-time processing *** computing has traditionally played an important role in establishing ***,fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility,location awareness,heterogeneity,scalability,low latency,and geographic ***,IoT networks are vulnerable to unwanted assaults because of their open and shared *** a result,various fog computing-based security models that protect IoT networks have been developed.A distributed architecture based on an intrusion detection system(IDS)ensures that a dynamic,scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is *** this study,we examined the time-related aspects of network traffic *** presented an intrusion detection model based on a twolayered bidirectional long short-term memory(Bi-LSTM)with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark *** showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy,precision,recall and F1 score.

关键词： Fog computing intrusion detection bi-LSTM attention mechanism

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AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

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Digital Communications and Networks 2024年第2期10卷 292-303页

作者： Yuteng Xiao Kaijian Xia Hongsheng Yin Yu-Dong Zhang Zhenjiang Qian Zhaoyang Liu Yuehan Liang Xiaodan Li School of Information and Control Engineering China University of Mining and TechnologyXuzhou221116China Department of Informatics University of LeicesterLeicesterLE17RHUK The Affiliated Changshu Hospital of Soochow University Changshu215500China School of Computer Science and Engineering Changshu Institute of TechnologySuzhou215500China

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other ***,it is important to construct a digital twin ***,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted *** this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)***,we fuse the spatial-temporal graph based on the interrelationship of spatial ***,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding ***,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)*** module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like *** dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted *** on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.

关键词： Adaptive adjacency matrix Digital twin Graph convolutional network Multivariate time series prediction Spatial-temporal graph

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Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

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computers, Materials & Continua 2023年第4期75卷 427-442页

作者： Reem Alkanhel El-Sayed M.El-kenawy D.L.Elsheweikh Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia

Traffic prediction of wireless networks attracted many researchersand practitioners during the past decades. However, wireless traffic frequentlyexhibits strong nonlinearities and complicated patterns, which makes it challengingto be predicted accurately. Many of the existing approaches forpredicting wireless network traffic are unable to produce accurate predictionsbecause they lack the ability to describe the dynamic spatial-temporalcorrelations of wireless network traffic data. In this paper, we proposed anovel meta-heuristic optimization approach based on fitness grey wolf anddipper throated optimization algorithms for boosting the prediction accuracyof traffic volume. The proposed algorithm is employed to optimize the hyperparametersof long short-term memory (LSTM) network as an efficient timeseries modeling approach which is widely used in sequence prediction *** prove the superiority of the proposed algorithm, four other optimizationalgorithms were employed to optimize LSTM, and the results were *** evaluation results confirmed the effectiveness of the proposed approachin predicting the traffic of wireless networks accurately. On the other hand,a statistical analysis is performed to emphasize the stability of the proposedapproach.

关键词： Network traffic soft computing LSTM metaheuristic optimization

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Network Management devices in an SDN environment 24

Network Management devices in an SDN environment

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24th International Conference on control Systems and computer science, CSCS 2023

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Soran Technical College Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

ISBN: (纸本)9798350313390

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management. © 2023 IEEE.

关键词： Network management

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A Survey on Security Issues in Cloud Systems 22

A Survey on Security Issues in Cloud Systems

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22nd RoEduNet Conference: Networking in Education and Research, RoEduNet 2023

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Soran Technical college Erbil Iraq Sutcu Imam University Computer Engineering Kahramanmaras Kahramanmaras Turkey

ISBN: (纸本)9798350393651

'The cloud' points out to servers, the databases and software that run on those servers. The Internet has always been constructed of infrastructure, servers and clients. Clients send their requests to servers, and servers reply, but cloud computing is distinct in the form that cloud servers are not just replying to requests with on-demand processing but they are saving data and running programs instead of the client. Cloud computing is a technology that is crossing a great expansion today. In cloud computing you can dynamically expand resources without knowledge of a new infrastructure, without developing new software or preparing new staff and to access such great technology the only things that are asked for are an Internet connection and an Internet browser. The goal of this survey is to present the different cloud security threats and recognize the proper security mechanism used to reduce them. © 2023 IEEE.

关键词： Cloud security

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