IEEE Transactions on Industrial Cyber-Physical Systems最新文献

Event-Triggered Predictive Control for Semi-Markov Jumping Networked Control Systems With Random DoS Attack 具有随机DoS攻击的半马尔可夫跳变网络控制系统的事件触发预测控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-06-10 DOI: 10.1109/TICPS.2025.3577549

Li Qiu;Baixi He;Chenmei Song;Zhen Huang;Jie Teng;Zongze Wu

{"title":"Event-Triggered Predictive Control for Semi-Markov Jumping Networked Control Systems With Random DoS Attack","authors":"Li Qiu;Baixi He;Chenmei Song;Zhen Huang;Jie Teng;Zongze Wu","doi":"10.1109/TICPS.2025.3577549","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3577549","url":null,"abstract":"Networked control systems (NCSs) are an important component of industrial cyber-physical systems (ICPSs). This paper proposes an event-triggered discrete-time stochastic semi-Markov hopping networked control systems robust predictive control strategy for ICPSs to address common parameter uncertainties and external disturbances. The control scheme aims to tackle the issues of randomness and time-varying characteristics inherent in ICPS, such as random time delays and denial-of-services (DoS) attacks in the channels of sensor-to-controller (S-C) and controller-to-actuator (C-A). To overcome the inherent bandwidth limitations, a dynamic event-triggered scheme is suggested to alleviate the network strain. The stability analysis gives a sufficient criterion for the <inline-formula><tex-math>$sigma$</tex-math></inline-formula>-error mean-square stability (<inline-formula><tex-math>$sigma$</tex-math></inline-formula>-MSS) of a semi-Markov jump linear system (s-MJLS) using Lyapunov function. Based on this analysis, a network predictive controller is designed to guarantee the robustness of the system. A linear switched reluctance motor (LSRM) system, as a typical application of ICPSs, is used for simulation and experimentation, thereby validating the practical efficacy and suitability of this approach.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"419-428"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314680","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

Data-Driven Group Formation Control of Cyber-Physical Systems via Distributed Cloud Computing 基于分布式云计算的信息物理系统数据驱动群体编队控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-04-16 DOI: 10.1109/TICPS.2025.3561726

Hongru Ren;Yinren Long;Hongyi Li;Tingwen Huang

引用次数: 0

A Relative-Error-Dependent TOD Protocol for Cyber-Physical Systems Under an Event-Triggered Communication 事件触发通信下网络物理系统的相对错误依赖TOD协议

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-04-03 DOI: 10.1109/TICPS.2025.3557733

Hongchenyu Yang;Chen Peng;Engang Tian

{"title":"A Relative-Error-Dependent TOD Protocol for Cyber-Physical Systems Under an Event-Triggered Communication","authors":"Hongchenyu Yang;Chen Peng;Engang Tian","doi":"10.1109/TICPS.2025.3557733","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3557733","url":null,"abstract":"To deal with different data magnitudes or measurement units of different system nodes, a novel relative-error-dependent try-once-discard (RED-TOD) communication protocol with event-triggered detectors is proposed to improve the accuracy and reliability of node selection for band-limited cyber-physical systems. With the combined effect of the absolute error and the relative error, a novel node activation condition is proposed to comprehensively reflect and fairly compare node transmission requirements. Under such a stricter scheduling rule, the node selection is more accurate as required and the available communication bandwidth is utilized with higher efficiency. Moreover, periodic sampling module and event-triggered detectors are placed before RED-TOD scheduling scheme to deal with redundancy and inaccurate transmissions of the existing variable sampling scheme. Taking the proposed scheduling scheme and non-small network-induced delay into account, an impulsive closed-loop system model is well established. Sufficient criteria for input-to-state stabilization are derived by employing the Lyapunov-Krasovskii functional approach. A searching algorithm is also presented to co-design optimized scheduler parameters and controller gains. Furthermore, to avoid continuous calculations, the next transmission instant and the dormant period of the event-triggered detector are predicted according to the present information carried by each node. Finally, an illustrative example is employed to demonstrate the effectiveness and superiority of the proposed scheduling method.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"318-328"},"PeriodicalIF":0.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839956","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

GenAI-Based Privacy-Preserving Transfer Learning 基于遗传算法的隐私保护迁移学习

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-04-02 DOI: 10.1109/TICPS.2025.3556993

Mostafa Hussien;Mohamed Cheriet;Kim Khoa Nguyen;Adel Larabi;Jungyeon Baek

{"title":"GenAI-Based Privacy-Preserving Transfer Learning","authors":"Mostafa Hussien;Mohamed Cheriet;Kim Khoa Nguyen;Adel Larabi;Jungyeon Baek","doi":"10.1109/TICPS.2025.3556993","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3556993","url":null,"abstract":"The rapid advancement of 5G technology has significantly accelerated the development of 6G standards, driving the need for even faster and more reliable connectivity. In this evolving landscape, the Integrated Sensing Digital Framework (ISDF) promises to revolutionize Industrial Cyber-Physical Systems (ICPS) by enabling unmatched real-time data acquisition, paving the way for groundbreaking advancements. ICPS nodes operate in diverse environments with varying levels of data availability. High-quality predictive models require large volumes of data, which may be abundant at some nodes and scarce at others. Instance-based transfer learning can address this disparity by transferring data from nodes with abundant data to those with limited data. However, this approach risks breaching data privacy, especially in sensitive ICPS applications such as industrial IoT (IIoT). To tackle this issue, we propose a novel privacy-preserving transfer learning approach based on generative models, specifically Generative Adversarial Networks (GANs). In this approach, a GAN is trained at a central center or node with access to large volumes of data. The generative model of the GAN is then transferred to nodes with data scarcity. Extensive experimental results on several real-world traffic load datasets confirm the effectiveness of this approach, highlighting its potential to enhance data-driven decision-making in ICPS while preserving data privacy.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"329-340"},"PeriodicalIF":0.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860862","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

NGMO: A Novel Geometric Mean Optimizer for Intrusion Detection in Industrial Cyber-Physical Systems NGMO：一种用于工业信息物理系统入侵检测的新型几何平均优化器

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-04-01 DOI: 10.1109/TICPS.2025.3556034

Yunhang Yao;Zhiyong Zhang;Kejing Zhao;Peng Wang;Ruirui Wu

{"title":"NGMO: A Novel Geometric Mean Optimizer for Intrusion Detection in Industrial Cyber-Physical Systems","authors":"Yunhang Yao;Zhiyong Zhang;Kejing Zhao;Peng Wang;Ruirui Wu","doi":"10.1109/TICPS.2025.3556034","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3556034","url":null,"abstract":"Industrial cyber-physical systems (CPS) are experiencing various malicious attacks and encountering increasing security challenges. Although machine learning-based intrusion detection systems can help users quickly detect attacks in industrial CPS, feature redundancy and the tuning of model hyperparameters hinder further detection performance. In this study, a Novel Geometric Mean Optimizer (NGMO) is designed to filter redundant industrial features while optimizing the hyperparameters of model. The proposed NGMO incorporates good point sets and dynamic opposition learning strategies during the population initialization and generation hopping phases to enhance the search capabilities of algorithm. Furthermore, the NGMO is combined with three gradient boosting decision tree models for intrusion detection in industrial CPS. Finally, four datasets from industrial scenarios and a real-world case are used to evaluate the effectiveness of NGMO. The experimental results show that NGMO can reduce time consumption while improving model detection accuracy. Therefore, the proposed NGMO can effectively enhance the security of industrial CPS.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"296-308"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817857","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

iCPS-DL: A Description Language for Autonomic Industrial Cyber-Physical Systems 自主工业信息物理系统的描述语言

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-03-31 DOI: 10.1109/TICPS.2025.3556065

Dimitrios Kouzapas;Christos Panayiotou;Demetrios G. Eliades

{"title":"iCPS-DL: A Description Language for Autonomic Industrial Cyber-Physical Systems","authors":"Dimitrios Kouzapas;Christos Panayiotou;Demetrios G. Eliades","doi":"10.1109/TICPS.2025.3556065","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3556065","url":null,"abstract":"Modern industrial systems require frequent updates to their cyber and physical infrastructures, often demanding considerable reconfiguration effort. This paper introduces the <italic>industrial Cyber-Physical Systems Description Language</i>, <inline-formula><tex-math>${mathsf{iCPS}}$</tex-math></inline-formula>-<inline-formula><tex-math>${mathsf{DL}}$</tex-math></inline-formula>, which enables autonomic reconfigurations for industrial Cyber-Physical Systems. The <inline-formula><tex-math>${mathsf{iCPS}}$</tex-math></inline-formula>-<inline-formula><tex-math>${mathsf{DL}}$</tex-math></inline-formula> maps an industrial process using semantics for physical and cyber-physical components, a state estimation model, and agent interactions. A novel aspect is using communication semantics to ensure <italic>live</i> interaction among distributed agents. Reasoning on the semantic description facilitates the configuration of the industrial process control loop. A Water Distribution Networks domain case study demonstrates <inline-formula><tex-math>${mathsf{iCPS}}$</tex-math></inline-formula>-<inline-formula><tex-math>${mathsf{DL}}$</tex-math></inline-formula>’s application.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"309-317"},"PeriodicalIF":0.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835457","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

Resilient Distributed Secondary Control of Battery Energy Storage Systems in Islanded Microgrids 孤岛微电网电池储能系统的弹性分布式二次控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-03-23 DOI: 10.1109/TICPS.2025.3572887

Sajad Koushkbaghi;Zhiyi Chen;Ali Moradi Amani;Mahdi Jalili;Xinghuo Yu

引用次数: 0

A Stability Condition for Asynchronous and Aperiodic Sampled-Data Cyber-Physical Systems Under DoS Attacks DoS攻击下异步非周期采样数据网络物理系统的稳定性条件

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-03-23 DOI: 10.1109/TICPS.2025.3573309

Liuyu Chen;Xiaodan Zhang;Feng Xiao

引用次数: 0

Homogeneous Polynomially Parameter-Dependent Fuzzy Switching Control of Nonlinear Cyber-Physical DC Microgrid System Against Multiple Malicious Attacks 非线性网络物理直流微电网系统抗多重恶意攻击的齐次多项式参数相关模糊切换控制

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-03-22 DOI: 10.1109/TICPS.2025.3572431

Fuyi Yang;Xiangpeng Xie;Yuanzheng Li

{"title":"Homogeneous Polynomially Parameter-Dependent Fuzzy Switching Control of Nonlinear Cyber-Physical DC Microgrid System Against Multiple Malicious Attacks","authors":"Fuyi Yang;Xiangpeng Xie;Yuanzheng Li","doi":"10.1109/TICPS.2025.3572431","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3572431","url":null,"abstract":"This paper focuses on the design of homogeneous polynomial parameter-dependent (HPPD) fuzzy switching security controller for nonlinear cyber-physical DC microgrid systems under multiple malicious attacks. Firstly, for the multiple cyber attack scenario with both denial of service (DoS) and false data injection (FDI), an HPPD fuzzy switching controller is designed, which can cope with DoS attack and has FDI attack signal compensation, and the corresponding augmented error system model of the DC microgrid is established. In addition to observing unmeasured system states and unknown FDI attack signals, this model also introduces homogeneous polynomial method and multi-mode fuzzy switching mechanism (MMFSM) to achieve accurate estimation and relaxation control. The so-called MMFSM aims to re-divide the space spanned by the fuzzy membership function into a set of non-overlapping subspaces, which can also be called different modes, by introducing a weight coefficient. Then, by designing a pair of exclusive gain matrices for each mode, a co-design method of HPPD-type multi-mode fuzzy switching security controller and state observer is proposed. More importantly, an improved multi-mode fuzzy switching mechanism (IMMFSM) is proposed by introducing a pair of weight coefficients. Compared with the previously proposed co-design method, IMMFSM can achieve lower conservatism. Finally, the effectiveness and advantages of the proposed theoretical results are verified and analyzed in a nonlinear cyber-physical DC microgrid system.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"386-396"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205804","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

Cyber-Physical Real-Time Digital Simulation for Cybersecurity Analysis in Microgrids 微电网网络安全分析的网络物理实时数字仿真

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-03-13 DOI: 10.1109/TICPS.2025.3569640

Dongmeng Qiu;Mengxiang Liu;Rui Zhang;Tianyu Luo;Antonio Griffo;Xin Zhang

{"title":"Cyber-Physical Real-Time Digital Simulation for Cybersecurity Analysis in Microgrids","authors":"Dongmeng Qiu;Mengxiang Liu;Rui Zhang;Tianyu Luo;Antonio Griffo;Xin Zhang","doi":"10.1109/TICPS.2025.3569640","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3569640","url":null,"abstract":"The rapid power grid digitalisation is increasingly addressing the importance of a real-time and high-fidelity cyber-physical co-simulation platform, which enables risk-free validation before the real-world implementation, especially for the cybersecurity research. Existing related works mainly focus on the impact analysis of attacks in massive power grid scenarios, while a thorough investigation regarding the implementation framework, cybersecurity analysis, and suitability assessment is lacking. Towards this end, we first propose a general implementation framework for real-time leader-follower and time-stepped co-simulation schemes, which are used to establish two cyber-physical co-simulation platforms based on off-the-shelf power and communication simulators. Then, thorough cybersecurity studies are conducted to showcase the relations between co-simulation configurations such as the communication network topology and attack compatibility. Finally, a set of metrics derived from synchronization computational overhead, latency, simulation scalability, and attack compatibility is presented to assess the suitability of a co-simulation platform for cybersecurity research. Recommendations are given to provide guidelines for industry practitioners and academia researchers in the establishment of cyber-physical co-simulation platforms that drive cybersecurity advancements.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"429-441"},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492480","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