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arXiv 2024年

作者： Javanmardi, Najmeh Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

This paper addresses the regulation and trajectory-tracking problems for two classes of weakly coupled electromechanical systems. To this end, we formulate an energy-based model for these systems within the port-Hamiltonian framework. Then, we employ Lyapunov theory and the notion of contractive systems to develop control approaches in the port-Hamiltonian framework. Remarkably, these control methods eliminate the need for solving partial differential equations or implementing any change of coordinates, and are endowed with a physical interpretation. We also investigate the effect of coupled damping on the transient performance and convergence rate of the closed-loop system. Finally, the applicability of the proposed approaches is illustrated in two applications of electromechanical systems via simulations. © 2024, CC BY.

关键词： Damping

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Teeth Segmentation from Bite-Wing X-Ray Images by Integrating Nested Dual UNet with Swin Transformers

Teeth Segmentation from Bite-Wing X-Ray Images by Integratin...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Li, Yubo Tian, Yibin Zhang, Zhiyuan Zhang, Xueyang Du, Bingran Zeng, Zhi School of Computer and Information Science Chongqing Normal University Chongqing401331 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Litemaze Technology Shenzhen518000 China School of Computing and Information Systems Singapore Management University Singapore487372 Singapore Shunde Hospital Department of Stomatology Foshan528000 China

ISBN: (纸本)9781665410205

In medical practice, the precision of image segmentation is crucial for diagnosis and treatment evaluations. Specifically, in dentistry, accurate teeth segmentation from bite-wing images is important for automatic and objective evaluations of root canal treatments. This study introduces Swin-U2 Net, a model merging the nested dual UNet with residual U-block and Swin Transformers. It combines the local feature extraction capability of the former and the global attention and context understanding of the latter. It has been evaluated for tooth root segmentation using 500 bite-wing dental x-ray images obtained from a root canal treatment clinic. It achieved the best segmentation outcome in terms of Intersection over Union (IOU) and the third best result in terms of Dice Similarity Coefficient (DSC) with the second least amount of network parameters among six UNet-like models, thus it is effective and efficient. © 2024 IEEE.

关键词： Image segmentation

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Multi-Modal Optimization of Stacked Chip Macro-Module Layout Based on Memristor-Inspired Evolutionary Game 4

Multi-Modal Optimization of Stacked Chip Macro-Module Layout...

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4th International Conference on Electronic Information engineering and Computer Communication, EIECC 2024

作者： Qiao, Kaikai Ma, Ben Chen, Mingze Ding, Ke Li, Changqing Duan, Shukai Wang, Lidan Southwest University College of Artificial Intelligence Chongqing China College of Artificial Intelligence Southwest University Chongqing China National Local Joint Engineering Research Center of of Intelligent Transmission and Control Technology Chongqing China Chongqing Key Laboratory of Brain-inspired Computing and Intelligent Chips Chongqing China Ministry of Education Chongqing China

ISBN: (纸本)9798331534622

As the complexity of chip design continues to increase, the stacking of multiple device layers in a three dimension(3D) architecture has emerged as a promising approach, which aims to optimize the placement and interconnections of large function blocks across the vertically-stacked device layers. Due to the complex interactions between layout and design constraints, traditional deterministic optimization often struggle to navigate its multi-modal search landscape effectively. Thus, we creatively propose the memristive evolutionary game: the diverse metal layers engage in a strategic interplay that determines the ownership hierarchy of chip macro modules and the 2D layout of these chip macro modules within each designated metal layer is orchestrated using evolutionary algorithm, which harness the power of game theoretic evolution to seek the optimal solution, balancing the objectives of minimizing layout area and wiring length. Upon comparison with alternative algorithms, the game evolution algorithm introduced in this paper exhibits superior optimization performance. © 2024 IEEE.

关键词： Memristors

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Kalman Filter Based Sensor Fusion for Omnidirectional Mechatronic System 35

Kalman Filter Based Sensor Fusion for Omnidirectional Mechat...

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35th International Conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Korotaj, Blaž Novoselnik, Branimir Baotić, Mato Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

The paper describes the sensor fusion for the newly developed omnidirectional mechatronic system. To that end, the kinematic model of the platform and the chosen configuration of omnidirectional Mecanum wheels is described, as well as the principle of operation of all system sensors. The expressions are given for a discrete linear Kalman filter that fuses measurements of a magnetometer and gyroscope, and for a discrete extended Kalman filter that estimates position and orientation of the platform using additional accelerometer measurements. To be able to express the measurement equation four additional states are added to the system model. The developed sensor fusion algorithm was implemented in MATLAB/Simulink programming environment, and very accurate simulation results are reported for estimation of position and orientation of the system. Finally, the real time experimental results are reported for a prototype of the omnidirectional mobile mechatronic system. ©2021 IEEE.

关键词： Discrete extended Kalman filter Mobile mechatronic system Omnidirectional drive Sensor fusion State estimation

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Secure Semantic Communication for Image Transmission in the Presence of Eavesdroppers

Secure Semantic Communication for Image Transmission in the ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Shunpu Tang Chen Liu Qianqian Yang Shibo He Dusit Niyato College of Information Science and Electronic Engineering Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Semantic communication (SemCom) has emerged as a key technology for the forthcoming sixth-generation (6G) network, attributed to its enhanced communication efficiency and robustness against channel noise. However, the open nature of wireless channels makes them vulnerable to eavesdropping, which poses a serious threat to privacy. To address this issue, we propose a novel secure semantic communication (SemCom) approach for image transmission, which integrates steganography technology to conceal private information within non-private images (host images). Specifically, we propose an invertible neural network (INN)-based signal steganography approach that embeds channel input signals of a private image into those of a host image before transmission. This ensures that the original private image can be reconstructed from the received signals at the legitimate receiver, while the eavesdropper can only decode the information of the host image. Simulation results demonstrate that the proposed approach maintains comparable reconstruction quality of both host and private images at the legitimate receiver, compared to scenarios without any secure mechanisms. Moreover, the results indicate that the eavesdropper is only able to reconstruct host images, showcasing the enhanced security provided by our approach.

关键词： Wireless communication Steganography Image communication Simulation Noise Receivers Semantic communication Robustness Security Image reconstruction

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Application of Extreme Learning Machine for Shunt Faults Detection and Classification in Three-phase Transmission Line Systems 3

Application of Extreme Learning Machine for Shunt Faults Det...

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3rd IEEE International Conference on Signal, control and Communication, SCC 2023

作者： Assadi, Khaoula Slimane, Jihane Ben Salhi, Salah University of Tunis El Manar National Engineering School of Tunis LR11ES20 Analysis Design and Control of Systems Laboratory Tunis1002 Tunisia Northern Border University Faculty of Computing and InformationTechnology Department of Computer Sciences Rafha91911 Saudi Arabia

ISBN: (纸本)9798350326390

The electrical power transmission lines play a crucial role in maintaining a continuous electricity supply. However, the exposed environment of these lines increases the risks of faults occurrence, necessitating prompt detection, and classification, to eliminate them within a specified time. In light of this, the present study introduces a methodology for the detection and classification of faults in a three-phase transmission line system employing the Extreme Learning Machine (ELM). A 220 kV, 300 km three-phase transmission line system was simulated in MATLAB/Simulink software, where the current and voltage signals were generated under different fault conditions including fault types, fault inception time, and fault resistance. The fundamental components of these signals were used as inputs in the ELM model. Different shunt fault types, including line-to-ground, line-to-line, double-line-to-ground, triple-line, and triple-line-to-ground were applied for fault detection and classification framework. Furthermore, the optimum number of hidden neurons in the ELM model was investigated in this study. In terms of the Mean Squared Error (MSE) and correlation coefficient, four ELM variants based on Sine, Sigmoid, Radial Basis, and Triangular Basis transfer functions were assessed for each module. The outcome of these metrics indicates that the ELM with the sigmoid model demonstrated superior performance compared to the other ELM models. Based on statistical metrics MSE, Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), and also the computational time, the efficiency of ELM-Sigmoid and state-of-the-art methods of Multi-Layer Perceptron Neural Network (MLPNN) and Radial Basis Function Neural Network (RBFNN) were compared and analyzed during training and testing phases. The results obtained revealed that the ELM-Sigmoid model outperforms the other models in the detection and classification of shunt faults with significant accuracy and fast computational speed. ©

关键词： Fault detection

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Research on Power Load Forecasting Based on Deep Learning 3

Research on Power Load Forecasting Based on Deep Learning

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3rd International Conference on Consumer Electronics and Computer engineering, ICCECE 2023

作者： Lin, Lanxin Yao, Jingxin Wang, Kun Zhejiang Gongshang University Sussex Artificial Intelligence Institute Hangzhou310000 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao Hebei066000 China University of Chinese Academy of Sciences Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China

ISBN: (纸本)9798350331578

In order to fully explore the time-series correlation of power load data and improve the prediction accuracy of power load, this paper proposes a neural network-based deep learning approach for power load prediction. Firstly, the relevant electric power data are obtained and divided into appropriate sample sizes, and the samples are normalized;then, a prediction model based on LSTM is built to explore the correlation between different features, and the corresponding model of this neural network is further trained and validated on the data test set;finally, a comparison between LSTM and other algorithms such as SVM, ANN, GAOS and GM are performed. The results show that the LSTM prediction algorithm can better track the trend of power load change, with higher prediction accuracy and efficiency. © 2023 IEEE.

关键词： Long short-term memory

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HRPDF: A Software-Based Heterogeneous Redundant Proactive Defense Framework for Programmable Logic controller

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Journal of Computer Science & Technology 2021年第6期36卷 1307-1324页

作者： Ke Liu Jing-Yi Wang Qiang Wei Zhen-Yong Zhang Jun Sun Rong-Kuan Ma Rui-Long Deng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China School of Information Systems Singapore Management UniversitySingapore 689867Singapore

Programmable logic controllers(PLCs)play a critical role in many industrial control systems,yet face increasingly serious cyber *** this paper,we propose a novel PLC-compatible software-based defense mechanism,called Heterogeneous Redundant Proactive Defense Framework(HRPDF).We propose a heterogeneous PLC architecture in HRPDF,including multiple heterogeneous,equivalent,and synchronous runtimes,which can thwart multiple types of attacks against PLC without the need of external *** ensure the availability of PLC,we also design an inter-process communication algorithm that minimizes the overhead of *** implement a prototype system of HRPDF and test it in a real-world PLC and an OpenPLC-based device,*** results show that HRPDF can defend against multiple types of attacks with 10.22%additional CPU and 5.56%additional memory overhead,and about 0.6 ms additional time overhead.

关键词： industrial control system programmable logic controller proactive defense heterogeneous redundant architecture

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Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

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Computers, Materials & Continua 2022年第4期71卷 1567-1580页

作者： E.Ahila Devi K.C.Ramya K.Sathesh Kumar Sultan Ahmad Seifedine Kadry Hyung Ju Park Byeong-Gwon Kang Department of Instrumentation and Control Engineering St.Joseph’s College of EngineeringChennai600119India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India School of Computing Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Applied Data Science Noroff University CollegeKristiansand4612Norway Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

A mobile ad hoc network(MANET)involves a group of wireless mobile nodes which create an impermanent network with no central authority and *** nodes in the MANET are highly mobile and it results in adequate network topology,link loss,and increase the re-initialization of the route discovery *** planning in MANET is a multi-hop communication process due to the restricted transmission range of the *** aided routing(LAR)is one of the effective routing protocols in MANET which suffers from the issue of high energy *** few research works have focused on resolving energy consumption problem in LAR,energy efficiency still remains a major design *** this aspect,this study introduces an energy aware metaheuristic optimization with LAR(EAMO-LAR)protocol for *** EAMO-LAR protocol makes use of manta ray foraging optimization algorithm(MRFO)to help the searching process for the individual solution to be passed to the LAR *** fitness value of the created solutions is determined next to pass the solutions to the objective *** MRFO algorithm is incorporated into the LAR protocol in the EAMO-LAR protocol to reduce the desired energy *** ensure the improved routing efficiency of the proposed EAMO-LAR protocol,a series of simulations take *** resultant experimental values pointed out the supreme outcome of the EAMO-LAR protocol over the recently compared *** resultant values demonstrated that the EAMO-LAR protocol has accomplished effectual results over the other existing techniques.

关键词： MANET routing lar protocol energy efficiency mrfo algorithm metaheuristics

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AoI Minimization for Air-Ground Integrated Sensing and Communication Networks with Jamming Attack

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IEEE Transactions on Vehicular Technology 2025年

作者： Mei, Hao Zhang, Haixia Zhou, Xiaotian Wang, Jing Shandong University School of Control Science and Engineering Shandong Jinan250061 China Shandong Key Laboratory of Intelligent Communication and Sensing-Computing Integration Shandong Jinan250061 China Shandong University School of Information Science and Engineering Shandong Qingdao266237 China

Air-ground integrated sensing and communication (AG-ISAC) networks utilize unmanned aerial vehicles (UAVs) equipped with ISAC units as aerial platforms in next-generation wireless systems, which can sense ground status information to the base stations (BSs) for further decision-making. Given that effective decisions rely on timely sensed data, the Age of Information (AoI) serves as a metric that precisely reflects the timeliness and effectiveness of the sensing and communication (S&C) process. However, recent research has paid little attention to AoI minimization in AG-ISAC networks, particularly in the presence of malicious attackers attempting to interfere S&C operations. To address this research gap, this paper considers AG-ISAC networks with S&C jamming attacks, a mission ISAC UAV senses tasks and transmits the sensed data to the BS, while a mobile UAV attacker sends jamming signals to degrade S&C performance and increase AoI. To solve this, we jointly design the trajectory and S&C transmit power of the mission UAV to mitigate S&C performance degradation to minimize the AoI. Nonetheless, the NP-hard and dynamic long-term nature of the formulated problem poses significant challenges. To tackle this troublesome problem, we develop an efficient solution using the deep reinforcement learning (DRL) technique. Specifically, we propose a twin-delayed deep deterministic policy gradient (TD3)-based trajectory design and power control algorithm (TD3-TP). In addition to this, we incorporate a reward-shaping mechanism to speed up the convergence of the algorithm. Simulation results demonstrate our algorithm achieves the fastest training speed and minimum AoI under attacks relative to four benchmark methods. © 1967-2012 IEEE.

关键词： Jamming

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