IEEE Transactions on Industrial Cyber-Physical Systems最新文献_第8页

Distributed Group Coordination of Random Communication Constrained Cyber-Physical Systems Using Cloud Edge Computing 利用云边缘计算实现随机通信受限网络物理系统的分布式群组协调

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-27 DOI: 10.1109/TICPS.2024.3419756

Hongru Ren;Yinren Long;Hui Ma;Hongyi Li

引用次数: 0

Privacy-Prioritized Model Aggregation in ICPS: A Novel Approach to Federated Learning Aggregation With Lime and Blockchain ICPS 中的隐私优先模型聚合：利用莱姆和区块链实现联合学习聚合的新方法

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-27 DOI: 10.1109/TICPS.2024.3419751

Arshia Aflaki;Hadis Karimipour;Thippa Reddy Gadekallu

引用次数: 0

Intelligent Collision-Free Formation Control of Ball-Riding Robots Using Output Recurrent Broad Learning in Industrial Cyber-Physical Systems 在工业网络-物理系统中使用输出递归广义学习实现滑球机器人的智能无碰撞编队控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-20 DOI: 10.1109/TICPS.2024.3416410

Ching-Chih Tsai;Hsu-Chih Huang;Hsing-Yi Chen;Chi-Chih Hung;Shih-Ting Chen

{"title":"Intelligent Collision-Free Formation Control of Ball-Riding Robots Using Output Recurrent Broad Learning in Industrial Cyber-Physical Systems","authors":"Ching-Chih Tsai;Hsu-Chih Huang;Hsing-Yi Chen;Chi-Chih Hung;Shih-Ting Chen","doi":"10.1109/TICPS.2024.3416410","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3416410","url":null,"abstract":"This article presents an intelligent collision-free formation control method of ball-riding robots using an output recurrent broad learning strategy (ORBLS) in industrial cyber-physical systems (ICPS). A cyber ORBLS is incorporated with the backstepping sliding mode formation control (BSMFC) and potential field theory, called ICPS ORBLS-BSMFC, in order to attain collision-free formation control for the multiple ball-riding robots with uncertainties for ICPS, the proposed cyber ORBLS-BSMFC computing method is employed to address the robust self-balancing formation control problem of ICPS gyro-stabilized robots. A bi-directed and connected graph is used to mathematically model the inverse-atlas self-balancing robots with uncertainties in formation encountering unknown frictions, mass variations. Taking the feedback signals from the physical world, Lyapunov stability theory is utilized to prove that the cyber ORBLS-BSMFC control law makes the system asymptotically stable. Three simulations and two experimental results will manifest the effectiveness, superiority and merits of the proposed ICPS ORBLS-BSMFC with obstacle avoidance. Through comparative studies, the advantages of the proposed ICPS ORBLS-BSMFC computing are validated to accomplish collision-free formation control for ball-riding robots.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"459-470"},"PeriodicalIF":0.0,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Intelligent Industrial Visual Monitoring and Maintenance Framework Empowered by Large-Scale Visual and Language Models 由大规模视觉和语言模型支持的智能工业视觉监控和维护框架

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-13 DOI: 10.1109/TICPS.2024.3414292

Huan Wang;Chenxi Li;Yan-Fu Li;Fugee Tsung

{"title":"An Intelligent Industrial Visual Monitoring and Maintenance Framework Empowered by Large-Scale Visual and Language Models","authors":"Huan Wang;Chenxi Li;Yan-Fu Li;Fugee Tsung","doi":"10.1109/TICPS.2024.3414292","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3414292","url":null,"abstract":"Industrial visual monitoring (IVM) is crucial for operation and maintenance, and artificial intelligence (AI) has excelled in this domain. As a revolutionary breakthrough in AI, large models are set to revolutionize IVM by advancing comprehensive automation and intelligence. This paper proposes an intelligent IVM and maintenance framework (IVMMF) empowered by large-scale visual and language models. Firstly, the proposed large-scale visual model comprehensively understands industrial images, providing accurate defect identification and descriptions. Subsequently, the local-knowledge-bases-based large language model was proposed to understand technical knowledge in specific fields, provide professional suggestions for engineers, and realize intelligent information interaction between the system and engineers. IVMMF achieves the intelligence of the entire process, including industrial image understanding, text dialogue, maintenance suggestions, and information communication. Finally, we construct a large-scale image-text IVM dataset, and the experiments demonstrate its exceptional performance, indicating its potential to transform the application paradigm in IVM.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"166-175"},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141453438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intrusion Detection in Cyber-Physical Grid Using Incremental ML With Adaptive Moment Estimation 利用具有自适应矩估计的增量式 ML 在网络物理网格中进行入侵检测

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-12 DOI: 10.1109/TICPS.2024.3413607

Zhijie Nie;Sagnik Basumallik;P. Banerjee;Anurag K. Srivastava

{"title":"Intrusion Detection in Cyber-Physical Grid Using Incremental ML With Adaptive Moment Estimation","authors":"Zhijie Nie;Sagnik Basumallik;P. Banerjee;Anurag K. Srivastava","doi":"10.1109/TICPS.2024.3413607","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3413607","url":null,"abstract":"A novel online and adaptive machine-learning approach for network intrusion detection is proposed in this work with a use case of unknown attack detection in the industrial cyber-physical power grid. Existing machine-learning (ML) based-intrusion detection systems in cyber-physical power systems rely on a fixed dataset with known attack anomalies for training. These approaches can lead to \u0000<italic>poor detection accuracy</i>\u0000 as unknown cyber-attacks target the system. As a result, these ML approaches need to be \u0000<italic>re-trained from scratch</i>\u0000. This research proposes an adaptive network intrusion detection technique that identifies anomalies in industrial cyber-power grids and is capable of detecting unknown attacks with significant accuracy. The proposed intrusion detector, a neural network with adaptive moment estimation, incorporates an \u0000<italic>adaptive incremental learning</i>\u0000 when exposed to a new vulnerability. It can be deployed at the device level in the phasor measurement network systems and evolves with the latest knowledge-base of cyber threats. The proposed approach is validated using a real cyber-physical simulation environment consisting of real-time digital simulator, multiple hardware phasor measurement units, and a network simulator under two different scenarios of unknown attacks, and extensive analysis is performed for different network architecture, training epochs, choice of loss functions, and the volume of data utilized. Results show that the incremental approach improves the accuracy of brute-force attacks to \u0000<inline-formula><tex-math>$>99.9%$</tex-math></inline-formula>\u0000 and penetration-test attacks to 63.7%. Further, the applicability of our method is validated on two publicly available datasets where incremental learning improved DDoS attack detection accuracy to 97.7%, UDP attacks to 73.1%, DoS attacks to 99% and Scan attacks to 94.2%.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"206-219"},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Early Detection of Cyber-Physical Attacks on Electric Vehicles Fast Charging Stations Using Wavelets and Deep Learning 利用小波和深度学习对电动汽车快速充电站的网络物理攻击进行早期检测

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-12 DOI: 10.1109/TICPS.2024.3413605

Ahmad M. Abu-Nassar;Walid G. Morsi

{"title":"Early Detection of Cyber-Physical Attacks on Electric Vehicles Fast Charging Stations Using Wavelets and Deep Learning","authors":"Ahmad M. Abu-Nassar;Walid G. Morsi","doi":"10.1109/TICPS.2024.3413605","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3413605","url":null,"abstract":"Transportation electrification plays an important role in the operation of the smart grid through the integration of the electric vehicle fast charging stations (EVFCSs), which allows the electric vehicles to provide regulation services to the grid through the vehicle-to-grid (V2G) concept. However, such an integration makes smart grid assets prone to cyber vulnerability threats. In this paper, a cyber-physical attack detection approach is developed to early detect such attacks. The proposed approach combines the continuous wavelet transform (CWT) and the convolution neural network (CNN) to provide an effective detection technique. The proposed detection approach has undergone rigorous testing that considered 420 realistic operational scenarios. Unlike in previous work, the proposed detection approach was found to be effective in automatically learning the salient features from the data as well as identifying the frequency bands that hold such features and using them in the classification process. Furthermore, this work investigated the cyber-attack detection accuracy using different time resolutions of smart meters. The results have shown that the proposed approach effectively detects cyber-physical attacks with an accuracy of 99.76% and a low computational time of 1.8 seconds.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"220-231"},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141725561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Byzantine-Resilient Distributed Bandit Online Optimization in Dynamic Environments 动态环境中的拜占庭弹性分布式匪徒在线优化

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-06-06 DOI: 10.1109/TICPS.2024.3410846

Mengli Wei;Wenwu Yu;Hongzhe Liu;Duxin Chen

{"title":"Byzantine-Resilient Distributed Bandit Online Optimization in Dynamic Environments","authors":"Mengli Wei;Wenwu Yu;Hongzhe Liu;Duxin Chen","doi":"10.1109/TICPS.2024.3410846","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3410846","url":null,"abstract":"We consider the constrained multi-agent online optimization problem in dynamic environments that are vulnerable to Byzantine attacks, where some infiltrated agents may deviate from the prescribed update rule and send arbitrary messages. The objective functions are exposed in a bandit form, i.e., only the function value is revealed to each agent at the sampling instance, and held privately by each agent. The agents only exchange information with their neighbors to update decisions, and the collective goal is to minimize the sum of the unattacked agents' objective functions in dynamic environments, where the same function can only be sampled once. To handle this problem, a Byzantine-Resilient Distributed Bandit Online Convex Optimization (BR-DBOCO) algorithm that can tolerate up to \u0000<inline-formula><tex-math>$mathcal {B}$</tex-math></inline-formula>\u0000 Byzantine agents is developed. Specifically, the BR-DBOCO employs the one-point bandit feedback (OPBF) mechanism and state filter to cope with the objective function, which cannot be explicitly expressed in dynamic environments and the arbitrary deviation states caused by Byzantine attacks, respectively. We show that sublinear expected regret is achieved if the accumulative deviation of the comparator sequence also grows sublinearly with a proper exploration parameter. Finally, experimental results are presented to illustrate the effectiveness of the proposed algorithm.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"154-165"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Risk Management for Demand Response in Multi-Utility Smart Grids 多公用事业智能电网中需求响应的动态风险管理

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-04-24 DOI: 10.1109/TICPS.2024.3392872

Fisayo Sangoleye;Eirini Eleni Tsiropoulou;Symeon Papavassiliou

{"title":"Dynamic Risk Management for Demand Response in Multi-Utility Smart Grids","authors":"Fisayo Sangoleye;Eirini Eleni Tsiropoulou;Symeon Papavassiliou","doi":"10.1109/TICPS.2024.3392872","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3392872","url":null,"abstract":"This research work is motivated by the need for effective demand response management (DRM) in smart grid systems. DRM is critical in optimizing the energy load by adjusting the energy prices and shifting high electricity demand to off-peak periods. This paper introduces a novel DRM model in a multi-user multi-utility company environment, considering the risk and uncertainty stemming from potential excessive energy demands, where each utility company is treated as a Common Pool of Resources (CPR). The risk-aware behavior of the consumers is captured using the Prospect Theory principles. Specifically, to model the interactions, we formulate a multi-leader multi-follower Stackelberg game involving the utility companies as leaders and the consumers as followers. The goal is to determine the optimal energy prices for the utility companies and the optimal amount of energy that each consumer purchases from these companies, considering their distributed decision-making process and exploring the non-cooperative Game Theory. The proposed DRM framework is assessed through numerical results, demonstrating its operational and performance efficiency. The results highlight the key benefits and tradeoffs of our model in comparison to alternative DRM strategies, emphasizing the significance of the presented approach in managing demand response effectively.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"98-107"},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140880720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Zero-Shot Learning Approach for Task Allocation Optimization in Cyber-Physical Systems 网络物理系统任务分配优化的零点学习方法

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-04-22 DOI: 10.1109/TICPS.2024.3392151

Eliseu Pereira;João Reis;Rosaldo J. F. Rossetti;Gil Gonçalves

{"title":"A Zero-Shot Learning Approach for Task Allocation Optimization in Cyber-Physical Systems","authors":"Eliseu Pereira;João Reis;Rosaldo J. F. Rossetti;Gil Gonçalves","doi":"10.1109/TICPS.2024.3392151","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3392151","url":null,"abstract":"The design and reorganization of Cyber-Physical Systems (CPSs) faces challenges due to the growing number of interconnected devices. To effectively handle disruptions and improve performance, rapid CPS design and development is crucial. The Task Resources Estimator and Allocation Optimizer (TREAO) addresses these challenges, by simulating and optimizing the tasks assignment to the CPS machines, recommending suitable software layouts for the CPS characteristics. It employs Zero-Shot Learning (ZSL) to predict task requirements in heterogeneous devices, enabling the characterization of software pipeline execution in distributed systems. The Genetic Algorithm (GA) component then optimizes the task assignment across available machines. Through experiments, the tool is evaluated for task characterization, CPS modeling and optimization performance. TREAO, when compared with similar tools, allows the simulation of more resource usage metrics (CPU, RAM, processing time and network delay) and increases flexibility in heterogeneous CPSs by predicting the task execution behavior and optimizing the task assignment.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"90-97"},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140826070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinating Systematic Grid-Forming Control of Hybrid Photovoltaic Plants in Weak Grids 弱电网中混合光伏发电站的系统并网协调控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2024-04-02 DOI: 10.1109/TICPS.2024.3384332

Shiwen Yu;Lina He

{"title":"Coordinating Systematic Grid-Forming Control of Hybrid Photovoltaic Plants in Weak Grids","authors":"Shiwen Yu;Lina He","doi":"10.1109/TICPS.2024.3384332","DOIUrl":"https://doi.org/10.1109/TICPS.2024.3384332","url":null,"abstract":"With the anticipated integration of numerous hybrid photovoltaic (PV) plants into subtransmission and distribution grids, managing a mix of inverter-based energy resources such as PV systems and battery energy storage systems (BESS) becomes crucial. These resources are required to effectively coordinate for primary frequency (f) and voltage (V) control and participate in power sharing, particularly in weaker grids. Currently, inverter-based energy resources are predominantly coordinated by droop-based control, which proves inadequate for hybrid PV plants in more resistive subtransmission and distribution grids due to the tightly coupled active power (P) and reactive power (Q). To overcome this challenge, this paper proposes an innovative coordinating systematic primary control strategy for grid-forming inverters in hybrid PV plants based on the multiple-input and multiple-output (MIMO) decoupling control. This method adaptively decouples the connected subtransmission or distribution grids during operation, with the aim of achieving effective, coordinated, and independent primary f and V regulation and accurate power sharing. For verification, comparative case studies are conducted in Simulink between the proposed control strategy and a conventional droop control scheme. The findings indicate that our proposed control method facilitates autonomous and independent primary f and V control, along with precise power sharing without relying on communication links. This results in markedly enhanced steady-state and dynamic performance. The decentralized primary controller offers simplicity, robustness, and cost-effectiveness, contributing to the stability and resilience of utility grids.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"81-89"},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0