{"title":"Privacy-Preserving Distributed Consensus via Inner Product Functional Encryption With Limited Communication","authors":"Jimin Wang;Nuerken Saireke;Yang Song","doi":"10.1109/TICPS.2026.3738327","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3738327","url":null,"abstract":"The problem of distributed consensus subject to privacy and limited communication has attracted widespread attention. Aiming at the privacy issue of distributed consensus with limited communication, this paper proposes a distributed consensus algorithm integrating inner product functional encryption with a trusted cloud server based on a dynamic encoder-decoder scheme. Each agent modifies its own initial state using the random vector generated by the cloud server, and then achieves privacy preservation through functional encryption. Considering that the quantization level of directed communication channels changes dynamically over iterations, the lower bound of the quantization level at each iteration to avoid quantizer saturation is derived theoretically, and the algorithm’s asymptotic convergence to average consensus is strictly proven. Meanwhile, it is verified that the proposed algorithm can effectively defend against external eavesdroppers and honest-but-curious agents, with further discussion on the necessary and sufficient conditions for the inferability of initial states. Finally, a numerical example validates the correctness of the theoretical analysis.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"1074-1083"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188344","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}
{"title":"Distributed Sequential State Estimation in Wireless Sensor Networks With Random Link Failures","authors":"Mingyan Zhu;Yaonan Wang;Yun Feng;Xu Fang;Jianan Huang","doi":"10.1109/TICPS.2026.3738335","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3738335","url":null,"abstract":"Wireless sensor networks (WSNs) are widely used in applications such as environmental monitoring, target tracking, and industrial automation. However, achieving accurate distributed state estimation in these networks is often challenged by the substantial communication and computational complexity inherent in conventional consensus-based methods. To address these limitations, this paper proposes a distributed state estimation algorithm that sequentially fuses local measurements with information exchanged among neighboring nodes. By eliminating batch fusion over fixed time intervals, the proposed approach significantly reduces communication and computational overhead while maintaining estimation accuracy in the presence of random link failures. A rigorous theoretical analysis derives sufficient conditions to ensure bounded estimation error covariance. Extensive numerical simulations further demonstrate the effectiveness of the proposed algorithm.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"1090-1100"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188345","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}
{"title":"Distributed CPS-Based Predefined-Time Control of Large-Scale Plug-and-Play Inverter Air Conditioner Clusters for Demand Response","authors":"Fan-Rong Qu;Zhi-Wei Liu;Yan-Wu Wang;Jia-Kai Wu","doi":"10.1109/TICPS.2026.3694620","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3694620","url":null,"abstract":"Industrial cyber-physical systems (CPS) increasingly rely on coordinated flexible loads to enhance grid stability and renewable energy integration. Among these, inverter air conditioners (IACs), as networked CPS agents, offer significant potential for demand response (DR) applications. This paper studies the predefined-time coordination of large-scale IAC clusters and proposes a CPS-based distributed control framework. By coupling the power tracking objective with user comfort consensus, the proposed approach coordinately regulates the power variation rates of individual air-conditioning units. This integrated design enables fast and accurate tracking of power commands at the system level within a predefined time, while simultaneously ensuring fairness in user comfort across the cluster. Rigorous convergence is established via Lyapunov-based stability analysis. To accommodate the plug-and-play nature of IACs, where units may dynamically join or leave the DR process, an adaptive shared-variable mechanism is further proposed to preserve network connectivity and coordination performance under dynamic topology variations. Extensive simulation studies demonstrate that the proposed framework effectively mitigates demand fluctuations and achieves rapid response to DR signals within the predefined time.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"324-334"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148171519","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}
{"title":"Policy-Prior-Guided Generative Coordination for Resilient Energy Management in Cyber-Physical Distributed Systems","authors":"Man Zhou;Xin Che","doi":"10.1109/TICPS.2026.3693245","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3693245","url":null,"abstract":"The dynamic network of heterogeneous and mobile energy nodes, such as drones, electric vehicles, and ground energy stations, forms the basis of air–ground collaborative cyber-physical energy systems. It is difficult to optimize system energy efficiency and economic operation while maintaining resilience under information and physical disturbances. The problem becomes more complex under strong spatiotemporal coupling, limited local information, and non-ideal communication. This paper proposes a strategy-prior-guided generative collaborative energy management framework, named PG-TSCD. The framework adopts a two-stage structure-aware decision process. At the system level, a spatiotemporal graph-based conditional diffusion model captures the dynamic coupling among nodes and global safety constraints. It describes the feasible scheduling space under complex constraints and generates a coordinated discharge and recharge power prior sequence. At the node level, each agent combines the global prior with incomplete local observations through a lightweight adaptive reconstruction module. It then produces executable scheduling actions that remain robust under disturbances. In this way, distributed agents achieve system objectives through coordinated decision making. Theoretical analysis shows that PG-TSCD approximates centralized optimal scheduling with a bounded performance gap and ensures stable distributed learning. Experiments show that the model converges in about 85 training rounds, reaches a peak energy efficiency of 3.5, and maintains a task completion rate above 93% under high load. The performance remains stable under 300 ms communication delay and 12% packet loss.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"455-469"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442210","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}
{"title":"Proactive Defence of Cyber-Physical Networks Against Coordinated Attacks With Optimal Resource Allocation","authors":"Min Du;Xin Zhang;David Flynn;Zidong Wang","doi":"10.1109/TICPS.2026.3705709","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3705709","url":null,"abstract":"Cyber-physical power systems (CPPSs) are more vulnerable to coordinated attacks on cyber-physical networks. In this context, this paper first assesses the impact of coordinated attacks and reveals the interdependence of cyber-physical networks in amplifying system vulnerability. To address this issue, a tri-level cyber-physical network defence (CPND) model is proposed to enable proactive defence of cyber-physical networks through optimal protection resource allocation against coordinated attacks. This model considers the cyber and physical network properties as well as their interdependence in CPPSs. Meanwhile, it incorporates the optimal allocation of control centres, providing more practical defence strategies against coordinated attacks. Then, a Column-and-Constraint Generation (C&CG) with optimality cuts algorithm is developed to solve the proposed CPND model, thereby improving computational efficiency. Numerical simulation results verify the superiority of the proposed approach.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"654-664"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148612985","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}
{"title":"Distributed Adaptive Observer-Based Security Control of Power Buffers in DC Microgrids Under Hybrid Attacks","authors":"Xiaotian Xu;Songlin Hu;Xia Zhou;Yu Huang;Xiaoli Chen","doi":"10.1109/TICPS.2026.3711974","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3711974","url":null,"abstract":"Power buffers enhance transient energy support in DC microgrids, but their distributed control loops are vulnerable to false-data-injection (FDI) and intermittent denial-of-service (DoS) attacks. This paper develops a resilient observer-based control framework with three core elements: DoS-dependent switching of the observer gain, online reconstruction of unknown FDI attacks, and feedforward compensation in the control input. The observer operates as a correction-based estimator during normal communication intervals and switches to a prediction mode during DoS intervals. Switched Lyapunov analysis proves uniformly ultimately bounded (UUB) stability under an average dwell-time condition. Simulations verify state-estimation performance, attack-reconstruction accuracy, compensation effectiveness, and improved robustness over a sliding-mode adaptive observer (SAO) benchmark.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"644-653"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613014","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}
{"title":"Toward a Standard Framework for Cyber-Secure Control of Converter-Dominated Microgrids","authors":"Sen Tan;Jian Sun;Peilin Xie","doi":"10.1109/TICPS.2026.3712304","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3712304","url":null,"abstract":"With the increasing integration of renewable energy sources, modern microgrids are dominated by power converters. However, due to their heavy reliance on digital communication, microgrids are more vulnerable to cyber-threats. While numerous research efforts have been made, existing studies primarily focus on attacks targeting single locations or specific converter types, often overlooking the holistic perspective of entire microgrids and the need for coordinated, multi-point defense strategies. In this paper, a comprehensive cyber-secure control framework is proposed to address and mitigate cyber-attacks across multiple microgrid locations, including sensor, actuator, and communication links for both grid-forming and grid-following converters. The proposed framework considers a confidence-based time varying graph theory, secure state estimation and full-state feedback control to strengthen microgrid security. First, the microgrid control structure and attack points are analyzed. Next, methods to counter these attacks are presented. Finally, the effectiveness of the proposed methods is validated on a dSPACE-based control platform. This research aims at establishing a framework for secure control design, providing recommendations to enhance the security of future microgrids.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"678-686"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613061","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}
{"title":"Formation Tracking of Open Multi-ASV Systems Subject to External Disturbances and Unmodeled Dynamics","authors":"Xiaodong Li;Guanghui Wen;Xiao Fang","doi":"10.1109/TICPS.2026.3726910","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3726910","url":null,"abstract":"This paper investigates the formation tracking problem for open multiple autonomous surface vessel (multi-ASV) systems subject to external disturbances and unmodeled dynamics. Unlike conventional multi-ASV systems with a fixed number of ASVs, an open multi-ASV system allows ASVs to leave or join the formation freely, which naturally leads to a dynamically evolving communication topology. These structural variations directly affect the information exchange and the control execution, introducing significant challenges to the achievement of formation tracking. To address these issues, a hierarchical control protocol is developed. First, a distributed observer is designed to estimate the formation tracking error and the velocity of the leader. Then, a virtual controller is constructed to generate reference velocity signals for each ASV. Based on the reference signal, a controller is subsequently designed to regulate the motion of each ASV. To compensate for unmodeled dynamics, a neural network-based estimator is incorporated into the control loop. Furthermore, an analytical method is proposed to characterize the evolution of the error system when an ASV leaves or joins the formation. By constructing appropriate inequalities and employing Lyapunov-based techniques, the formation tracking problem of open multi-ASV systems with external disturbances and unmodeled dynamics is effectively addressed using the proposed control protocol. The effectiveness of the theoretical results is validated through a simulation example.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"868-877"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925303","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}
{"title":"Resilient Containment Control of Stochastic Multiagent Systems Under Deception Attacks: An Event-Triggered Impulsive Framework","authors":"Le You;Yiyan Han;Xin Wang","doi":"10.1109/TICPS.2026.3724987","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3724987","url":null,"abstract":"This paper addresses the secure containment control problem for stochastic multi-agent systems (SMASs) under the threat of malicious deception attacks, environmental noise, and system uncertainties. A resilient event-triggered impulsive control (ETIC) protocol is established to counteract these adverse effects while significantly optimizing communication resource utilization. By utilizing Lyapunov stability theory and Linear Matrix Inequality (LMI) techniques, we derive novel sufficient conditions that ensure the stability and precise containment of the multi-agent network. Furthermore, the underlying event-triggering mechanism is theoretically verified to be free of Zeno behavior, making it viable for practical engineering applications. Finally, the effectiveness and communication efficiency of the developed ETIC framework are illustrated via two numerical simulation examples.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"825-832"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925387","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}
{"title":"A New Unified Methodology for Physics and Data Hybrid Modeling—Showcase in Maritime","authors":"Tongtong Wang;Qin Liang;Jinhua She;Houxiang Zhang","doi":"10.1109/TICPS.2026.3728743","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3728743","url":null,"abstract":"Hybrid modeling, which integrates physics-based knowledge with data-driven learning, has emerged as a promising paradigm for complex industrial cyber-physical systems where neither approach alone is sufficient. However, most existing works focus on exploring new hybrid algorithms for specific tasks, while limited attention has been given to systematic guidance for hybrid model design across heterogeneous applications. This paper introduces a unified hybrid modeling methodology that characterizes hybrid systems along two fundamental dimensions: the functional modes (complementary, cooperative, and competitive) and the canonical topologies (sequential, parallel, and embedded). This formulation enables systematic reasoning about how physics and data should interact under different knowledge–data conditions. The methodology is domain-agnostic and applicable to a wide range of industrial cyber-physical systems. Maritime applications are used in this study as a stress-test domain due to their safety-critical nature, complex environmental interactions, and limited availability of large datasets. Four representative case studies, including motion control, dynamics identification, fuel consumption estimation, and sea-state prediction, demonstrate how different hybrid configurations emerge naturally under varying knowledge and data availability. The results show that the proposed framework provides practical guidance for selecting appropriate hybrid modeling strategies in real-world engineering applications.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"887-898"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985711","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}