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State-feedback memory control for uncertain cyber-physical systems under Denial-of-Service attacks*

IFAC-PapersOnLine 2023年第2期56卷 544-549页

作者： Pedro M. Oliveira Ricardo C.L.F. Oliveira Jonathan M. Palma Márcio J. Lacerda Control and Modelling Group (GCOM) Department of Electrical Engineering Federal University of São João del-Rei - UFSJ São João del-Rei MG Brazil School of Electrical and Computer Engineering University of Campinas - UNICAMP Campinas São Paulo Brazil Faculty of Engineering Universidad de Talca Curicó Chile

This paper tackles the problem of state-feedback control for uncertain cyber-physical systems with the presence of Denial-of-Service attacks. The closed-loop stability is guaranteed through a new state-feedback packet-based strategy that utilizes past states (memory) to artificially enrich the control dynamics. The presence of an energy-bounded attacker is assumed and the closed-loop system under attack is modeled as an uncertain switched system. A less conservative stability analysis condition based on the Lyapunov theory is used as starting point for the synthesis conditions, which are formulated in terms of Linear Matrix Inequalities. Numerical experiments are conducted to illustrate the technique's effectiveness and perform comparisons with packet-based methods from the literature.

关键词： Robust control Cyber-physical systems DoS attacks Linear Matrix Inequalities control with memory

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Design and Analysis of Weather Parameters Using MEMS Technology with Suitable Characteristics for Integration into a Single Chip for Environment Monitoring

Design and Analysis of Weather Parameters Using MEMS Technol...

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Smart Technologies and Systems for Next Generation Computing (ICSTSN), International Conference on

作者： Abdurrashid S. Hassan Vimala A. Juliet G. Pius Agbulu G. Joselin Retna Kumar Raghavendra Reddy N V S Gunasekar Department of Electronics and Control/Instrumentation Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Mechatronic Engineering School of Engineering Sciences & Technology Chinhoyi University of Technology Chinhoyi Zimbabwe Department of Electronics and Instrumentation Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Mechanical Engineering RV Institute of Technology and Management Karnataka India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798350391565

ISBN: (纸本)9798350391572

This study designs and simulates weather parameters using MEMS technology with suitable characteristics for integration into a single chip for environment monitoring. The sensing and heating filament of the temperature sensor was designed using a thin film platinum resistor, examining its ability to experience stability, increase in resistivity, accuracy, and free-contamination. The temperature sensing and heating element are based on platinum RTD (Resistance Temperature Detector) with meander shape and aluminum as the bonding pad connecting the sensor to the external circuit. A capacitive humidity sensor is implemented in consolidation with a piezoresistive pressure sensor with a square membrane. The capacitive humidity sensor with hole pattern at the upper plate and a polyimide serves as water absorbent sandwiched between the electrodes. The simulation analysis was conducted using finite element analysis in COMSOL Multiphysics version 6.0 . It was observed that the temperature increases from -100oC to - 20oC, and 10oC to 50oC respectively as a result of deviation in relative humidity in the troposphere, and atmosphere. The average changes in capacitances were found at 0.0713/%RH, while the pressure was examined to vary from 1050hPa to 5hPa in a step of 200hPa with a sensitivity of 11.50mv/bar.

关键词： Temperature sensors Temperature Platinum Terrestrial atmosphere Humidity Stability analysis Finite element analysis

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Modeling Method of Aircraft Simulation Based on Formal Description of Petri Net 18th

Modeling Method of Aircraft Simulation Based on Formal Des...

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18th Chinese Intelligent Systems Conference, CISC 2022

作者： Zhan, Tianming Huang, Yu Geng, Huapin Tong, Jiahui TAIJI Computer Co. Ltd Beijing100102 China Peking University Beijing100871 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100190 China Beijing Electro-Mechanical Engineering Institute Beijing102299 China

ISBN: (纸本)9789811962028

The simulation of aircraft guidance and control system has characteristics such as multiple model classification, large parameter influence,complex information interaction and so on. The traditional code-level model development method has many limitations, such as time consuming, low reusability, low modeling efficiency, and model quality can not be guaranteed. Based on the concurrency, graphic representation, mathematics and simulation characteristics of Petri net, this paper studies the aircraft simulation modeling method of formal description based on Petri net, constructs a general modeling development and integration software tool that can carry out component, parametric and graphical modeling, solves the problems of multi granularity model modeling and automatic generation of real-time simulation model code, and realizes the visual graphic modeling and comprehensive integration of different granularity models such as components, modules and meta models. The research method has been successfully applied in the simulation modeling of an aircraft. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Petri nets

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Resource-Efficient and Self-Adaptive Quantum Search in a Quantum-Classical Hybrid System

arXiv

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arXiv 2024年

作者： Jiang, Zihao Du, Zefan Ruan, Shaolun Chen, Juntao Wang, Yong Cheng, Long Buyya, Rajkumar Mao, Ying The Department of Computer and Information Science Fordham University New York City United States The School of Computing and Information Systems Singapore Management University Singapore The School of Control and Computer Engineering North China Electric Power University Beijing China The School of Computing and Information Systems The University of Melbourne Australia

Over the past decade, the rapid advancement of deep learning and big data applications has been driven by vast datasets and high-performance computing systems. However, as we approach the physical limits of semiconductor fabrication in the post-Moore's Law era, questions arise about the future of these applications. In parallel, quantum computing has made significant progress with the potential to break limits. Major companies like IBM, Google, and Microsoft provide access to noisy intermediate-scale quantum (NISQ) computers. Despite the theoretical promise of Shor's and Grover's algorithms, practical implementation on current quantum devices faces challenges, such as demanding additional resources and a high number of controlled operations. To tackle these challenges and optimize the utilization of limited onboard qubits, we introduce ReSaQuS, a resource-efficient index-value searching system within a quantum-classical hybrid framework. Building on Grover's algorithm, ReSaQuS employs an automatically managed iterative search approach. This method analyzes problem size, filters less probable data points, and progressively reduces the dataset with decreasing qubit requirements. Implemented using Qiskit and evaluated through extensive experiments, ReSaQuS has demonstrated a substantial reduction, up to 86.36% in cumulative qubit consumption and 72.72% in active periods, reinforcing its potential in optimizing quantum computing application deployment. © 2024, CC BY.

关键词： Hybrid systems

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Network Slice Degradation Probability as a Metric for Defining Slice Performance Isolation 21st

Network Slice Degradation Probability as a Metric for Defini...

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21st International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2021 and 14th Conference on Internet of Things and Smart Spaces, ruSMART 2021

作者： Polyakov, Nikita Yarkina, Natalia Samouylov, Konstantin Koucheryavy, Yevgeni RUDN University Miklukho-Maklaya Street 6 Moscow117198 Russia Unit of Electrical Engineering Tampere University Tampere33720 Finland Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences 44-2 Vavilov Street Moscow119333 Russia

ISBN: (纸本)9783030977764

Slice isolation is a key feature of the network slicing technique and refers to protecting slices from negative impact of fault, attack or workload increase in other slices. Dynamic resource slicing policies, although provide efficient multiplexing and resource utilization, may lead to situation when a traffic surge in one slice hinders performance of other slices. The level of performance isolation cannot be specified and evaluated without defining an adequate metric. This paper addresses network slice degradation probability as a metric for defining performance isolation of slice. We use teletraffic theory to derive an analytical expression for the degradation probability in a single slice. © 2022, Springer Nature Switzerland AG.

关键词： Probability

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A software-defined security middle platform architecture 22

A software-defined security middle platform architecture

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5th International Conference on computer Science and Software engineering, CSSE 2022

作者： Qiu, Rixuan Qin, Yongtai Li, Yuancheng Zhou, Xin Fu, Junfeng Li, Wei Yan, Juan Shi, Jie State Grid Jiangxi Information & Telecommunication Company China School of Control and Computer Engineering North China Electric Power University China State Grid Jiangxi Electric Power Company Yingtan Power Supply Branch China Co. Ltd. China

ISBN: (纸本)9781450397780

In recent years, with the increase in the variety of communication devices, as well as the rapid development of the Internet of Things, edge computing, and machine learning, the existing security solutions can neither solve the problem of increasing fragmentation of security needs and security scenarios, nor the problem of the mismatch between security protection means and business scenarios, so the new software-defined security middle platform architecture is proposed. The infrastructure plane is connected to the architecture through network function virtualization. The security middle platform has the advantages of both the data middle platform and the business middle platform is designed to solve the fragmentation problem. Hybrid cloud environment is designed according to the cost, expansion, and security requirements. The control plane solves the matching problem for the middle platform resource pool through flexible and intelligent scheduling. The small forward platform design of the application plane further reduces the development cost. © 2022 ACM.

关键词： Network function virtualization

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Leveraging 3D blendshape for facial expression recognition using CNN

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Science China(Information Sciences) 2020年第2期63卷 101-103页

作者： Sa WANG Zhengxin CHENG Xiaoming DENG Liang CHANG Fuqing DUAN Ke LU College of Artificial Intelligence Beijing Normal University Bejing Key Laboratory of Human-Computer Interactions Institute of Software Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

Dear editor,Recently, facial expression recognition (FER) has drawn increasing attention owing to its widespread application in many fields such as human-machine interaction, assistive healthcare, psychology, and onli... 详细信息

关键词： image Leveraging 3D blendshape for facial expression recognition using CNN

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Deep Learning for Personalized Electrocardiogram Diagnosis: A Review

arXiv

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arXiv 2024年

作者： Ding, Cheng Yao, Tianliang Wu, Chenwei Ni, Jianyuan Department of Biomedical Engineering Georgia Institution of Technlogy Atlanta United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University No. 1239 Siping Road Shanghai200092 China Department of Biomedical Engineering University of Rochester Rochester United States Department of Information Technology and Computer Science Juniata College Huntingdon United States

The electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep learning has heralded a revolutionary era in medical data analysis, particularly in the domain of ECG diagnostics. However, inter-patient variability prohibit the generalibility of ECG-AI model trained on a population dataset, hence degrade the performance of ECG-AI on specific patient or patient group. Many studies have address this challenge using different deep learning technologies. This comprehensive review systematically synthesizes research from a wide range of studies to provide an in-depth examination of cutting-edge deep-learning techniques in personalized ECG diagnosis. The review outlines a rigorous methodology for the selection of pertinent scholarly articles and offers a comprehensive overview of deep learning approaches applied to personalized ECG diagnostics. Moreover, the challenges these methods encounter are investigated, along with future research directions, culminating in insights into how the integration of deep learning can transform personalized ECG diagnosis and enhance cardiac care. By emphasizing both the strengths and limitations of current methodologies, this review underscores the immense potential of deep learning to refine and redefine ECG analysis in clinical practice, paving the way for more accurate, efficient, and personalized cardiac diagnostics. © 2024, CC BY.

关键词： Generative adversarial networks

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Condition Monitoring & Fault Detection in Photovoltaic Modules Using Machine Learning 1

Condition Monitoring & Fault Detection in Photovoltaic Modul...

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1st International Conference on Sustainable Technology for Power and Energy Systems, STPES 2022

作者： Tyagi, Shivam Dhingra, Bhavya Tomar, Anuradha Netaji Subhas University of Technology Department of Computer Science Delhi78 India Netaji Subhas University of Technology Department of Electrical Engineering Delhi78 India Netaji Subhas University of Technology Department of Inst. and Control Engg. Delhi78 India

ISBN: (纸本)9781665459150

There has been a significant increase in the use of renewable energy solutions such as Photovoltaic (PV) power plant projects to decrease the dependency on fossil fuels while still meeting the global energy demands. However, these technologies come with their own set of problems. Condition monitoring and maintenance of PV modules are one of the challenges that need to be tackled to make these new energy solutions even more efficient. The cleaning of PV modules and the maintenance of hardware components used in a power plant are significantly important to the total energy yield and efficiency of the project. This paper provides a detailed look into the application of machine learning algorithms for condition monitoring and fault detection in photovoltaic modules. This paper employs various regression models to predict the power output of the PV modules accurately. The model takes inputs from the inverter connected to an array mesh of PV modules and applies a trained prediction model that can work in real-time. The system is based on comparing linear, Bayesian and non-linear regression models on their ability to explain the variance of the yield by PV modules. © 2022 IEEE.

关键词： Fault detection

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Integrated fault-tolerant control of assembly and automated guided vehicle-based transportation layers

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International Journal of computer Integrated Manufacturing 2022年第4-5期35卷 409-426页

作者： Pawel Majdzik Marcin Witczak Bogdan Lipiec Zbigniew Banaszak a Department of Electronics and Computer Science Koszalin University of Technology Koszalin Polandb Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland

ABSTRACTABSTRACTThe paper concerns the digital twin design and fault-tolerant control of a production system. The real laboratory system under consideration consists of two subsystems: an assembly part and an automated guided vehicle transportation one. The proposed approach focuses, simultaneously, on both concurrency and synchronization problems as they are inevitable in such a kind of modern systems. The research contribution deals with the development of an analytical description of both an assembly system and a multiple automated guided vehicles transportation layer along with algorithms that are able to determine an optimum sequence of starting individual operations. Subsequently, diagnostics and fault-tolerant control schemes are elaborated and applied to the two-layer system being investigated. The core advantage of the proposed approach is that it can compensate or eliminate the impact of some faults, e.g. delays occurring in the assembly unit or reduced velocities of transportation means. This makes it possible to keep the desired schedule as far as possible. The paper concludes with a series of illustrative use cases and comparisons which exhibit the performance of the novel approach in both cases, i.e. faulty and fault-free.

关键词： Fault-tolerant control assembly system automated guided vehicles system digital twin concurrency synchronization predictive control

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