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Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 344-361页

作者： Yunfeng Hu Chong Zhang Bo Wang Jing Zhao Xun Gong Jinwu Gao Hong Chen State Key Laboratory of Automotive Simulation and Control Jilin UniversityJilin UniversityChangchun 130025China College of Communication engineering Jilin UniversityJilin UniversityChangchun 130025China department of electromechanical engineering University of MacaoMacao 999078China School of Artificial Intelligence Jilin UniversityChangchun 130012China IEEE College of Electronics and information engineering Tongji UniversityShanghai 200092China

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

关键词： Adaptive control control system synthesis data-driven iterative learning control neurocontroller nonlinear discrete time systems

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State-of-charge Balance Control and Safe Region Analysis for Distributed Energy Storage Systems with Constant Power Loads

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1733-1745页

作者： Yijing Wang Yangzhen Zhang Zhiqiang Zuo Xialin Li department of Electrical and information engineering Tianjin UniversityTianjin 300384China

This paper presents a fully distributed state-of-charge balance control (DSBC) strategy for a distributed energy storage system (DESS). In this framework, each energy storage unit (ESU) processes the state-of-charge (SoC) information from its neighbors locally and adjusts the virtual impedance of the droop controller in real-time to change the current sharing. It is shown that the SoC balance of all ESUs can be achieved. Due to virtual impedance, voltage deviation of the bus occurs inevitably and increases with load power. Meanwhile, widespread of the constant power load (CPL) in the power system may cause instability. To ensure reliable operation of DESS under the proposed DSBC, the concept of the safe region is put forward. Within the safe region, DESS is stable and voltage deviation is acceptable. The boundary conditions of the safe region are derived from the equivalent model of DESS, in which stability is analyzed in terms of modified Brayton-Moser's criterion. Both simulations and hardware experiments verify the accuracy of the safe region and effectiveness of the proposed DSBC strategy.

关键词： Constant power load(CPL) distributed control distributed energy storage system(DESS) safe region state-of-charge(SoC)

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Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

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CES Transactions on Electrical Machines and Systems 2024年第2期8卷 202-215页

作者： Yuxuan Du Wenxiang Zhao Yihua Hu Jinghua Ji Tao Tao IEEE School of Electrical and information engineering Jiangsu University department of engineering King’s College London

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control *** is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are *** ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is *** likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical ***-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be *** focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation *** paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past *** strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and *** paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in ***,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

关键词： Fault-tolerant Motor drive Operation quality Inverter failure

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MarkINeRV: A Robust Watermarking Scheme for Neural Representation for Videos Based on Invertible Neural Networks

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Computers, Materials & Continua 2024年第9期80卷 4031-4046页

作者： Wenquan Sun Jia Liu Lifeng Chen Weina Dong Fuqiang Di department of Cryptographic engineering Engineering University of PAPXi’an710086China department of Cryptographic engineering Key Laboratory for Cryptology and Information SecurityXi’an710086China

Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue *** response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of *** is just that the information flow is in the opposite ***,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse *** paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video *** results demonstrate its efficacy in extracting watermarking information for copyright protection of *** represents a pioneering investigation into copyright issues surrounding NeRV.

关键词： Invertible neural network neural representations for videos watermarking robustness

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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed department of Computer engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan department of information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan department of information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia department of Management information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia department of Software engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan department of Electrical engineering Balochistan University of information Technology Engineeringand Management SciencesQuetta87300Pakistan department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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Near-field wideband beam training for ELAA with uniform circular array

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Science China(information Sciences) 2024年第6期67卷 370-383页

作者： Yuhao CHEN Linglong DAI department of Electronic engineering Tsinghua UniversityBeijing National Research Center for Information Science and Technology (BNRist)

Extremely large-scale antenna array(ELAA) at millimeter wave(mmWave) and Terahertz(THz)band has been considered a key technology for combating high attenuation in high-frequency bands in future6G communications. Uniform circular arrays(UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing(FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDFbased beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.

关键词： extremely large-scale antenna array (ELAA) uniform circular array (UCA) near-field wideband beam training

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A Novel Approach to Energy Optimization:Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

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Computers, Materials & Continua 2024年第5期79卷 2945-2970页

作者： Muhammad Salman Qamar Ihsan ulHaq Amil Daraz Atif MAlamri Salman A.AlQahtani Muhammad Fahad Munir department of Electrical and Computer engineering International Islamic UniversityIslamabad44000Pakistan School of information Science and engineering NingboTech UniversityNingbo315100China Software engineering department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia Computer engineering department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia

In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing ***,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable *** data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network *** mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring *** unique determination of this study is the shortest path to reach *** the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static *** this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the *** methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide *** addition,a method of using MS scheduling for efficient data collection is *** simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.

关键词： Wireless Sensor Networks(WSNs) mobile sink(MS) rendezvous point(RP) machine learning Artificial Neural Networks(ANNs)

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RWNeRF:Robust Watermarking Scheme for Neural Radiance Fields Based on Invertible Neural Networks

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Computers, Materials & Continua 2024年第9期80卷 4065-4083页

作者： Wenquan Sun Jia Liu Weina Dong Lifeng Chen Fuqiang Di department of Cryptographic engineering Engineering University of PAPXi’an710086China department of Cryptographic engineering Key Laboratory of PAP for Cryptology and Information SecurityXi’an710086China

As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly *** response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network *** 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D ***,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s *** module restores distorted images through neural network processing before watermark ***,embedding watermarks in each training image enables watermark information extraction from multiple *** proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,*** results demonstrate the efficacy of our scheme in enhancing copyright protection.

关键词： Neural radiance fields 3D scene robust watermarking invertible neural networks

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Low-Brightness Object Recognition Based on Deep Learning

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Computers, Materials & Continua 2024年第5期79卷 1757-1773页

作者： Shu-Yin Chiang Ting-Yu Lin department of information and Telecommunications engineering Ming Chuan UniversityTaoyuan City333Taiwan

This research focuses on addressing the challenges associated with image detection in low-light environments,particularly by applying artificial intelligence techniques to machine vision and object recognition *** primary goal is to tackle issues related to recognizing objects with low brightness *** this study,the Intel RealSense Lidar Camera L515 is used to simultaneously capture color information and 16-bit depth information *** detection scenarios are categorized into normal brightness and low brightness *** the system determines a normal brightness environment,normal brightness images are recognized using deep learning *** low-brightness situations,three methods are proposed for *** first method is the SegmentationwithDepth image(SD)methodwhich involves segmenting the depth image,creating amask from the segmented depth image,mapping the obtained mask onto the true color(RGB)image to obtain a backgroundreduced RGB image,and recognizing the segmented *** second method is theHDVmethod(hue,depth,value)which combines RGB images converted to HSV images(hue,saturation,value)with depth images D to form HDV images for *** third method is the HSD(hue,saturation,depth)method which similarly combines RGB images converted to HSV images with depth images D to form HSD images for *** experimental results,in normal brightness environments,the average recognition rate obtained using image recognition methods is 91%.For low-brightness environments,using the SD method with original images for training and segmented images for recognition achieves an average recognition rate of over 82%.TheHDVmethod achieves an average recognition rate of over 70%,while the HSD method achieves an average recognition rate of over 84%.The HSD method allows for a quick and convenient low-light object recognition *** research outcome can be applied to nighttime surveillance systems or nighttime road safety systems

关键词： Low-brightness depth image image segmentation image recognition HDV HSD

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Data delivery delay and cross-layer packet size analysis for reliable transmission of Licklider transmission protocol in space networks

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Science China(information Sciences) 2024年第9期67卷 229-244页

作者： Guannan YANG Ruhai WANG Kanglian ZHAO Wenfeng LI Dong YAN School of information engineering Nanjing University of Finance and Economics Drayer department of Electrical and Computer engineering Lamar University School of Electronic Science and engineering Nanjing University Beijing Aircraft Overall Design department

Delay/disruption tolerant networking(DTN) is proposed as a networking architecture to overcome challenging space communication characteristics for reliable data transmission service in presence of long propagation delays and/or lengthy link disruptions. Bundle protocol(BP) and Licklider Transmission Protocol(LTP) are the main key technologies for DTN. LTP red transmission offers a reliable transmission mechanism for space networks. One of the key metrics used to measure the performance of LTP in space applications is the end-to-end data delivery delay, which is influenced by factors such as the quality of spatial channels and the size of cross-layer packets. In this paper, an end-to-end reliable data delivery delay model of LTP red transmission is proposed using a roulette wheel algorithm, and the roulette wheel algorithm is more in line with the typical random characteristics in space networks. The proposed models are validated through real data transmission experiments on a semi-physical testing platform. Furthermore, the impact of cross-layer packet size on the performance of LTP reliable transmission is analyzed, with a focus on bundle size, block size, and segment size. The analysis and study results presented in this paper offer valuable contributions towards enhancing the reliability of LTP transmission in space communication scenarios.

关键词： Licklider transmission protocol DTN bundle protocol cross-layer packets size space communication

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