Pub Date : 2024-12-13DOI: 10.1109/JSYST.2024.3506812
Lin Sun;Mingming Wang;Chong Wu;Yuan Ping;Juntong Qi
When information interaction occurs among agents, the communication network could be attacked or the signal interrupted, culminating in systemic instability and mission failure. Therefore, this article proposes $mathcal {H}_{infty }$ resilient bipartite control method to address the security problem of network information interaction among agents within competitive and cooperative multiagent systems. When the communication networks among agents are subject to a replay attack, the system model integrating multisensor weight fusion with an unknown input leader is established first. Then, a detection fusion algorithm is proposed to simultaneously uncover attacker behavior and identify tampered sensors. Considering the intermittent or interrupted communication resulting from the time variability of topology switching among agents, the switching topology is modeled by a semi-Markov process within a signed graph having positive and negative interaction weights. Subsequently, a distributed observer is designed to estimate the unknown input leader, utilizing the semi-Markov interactions among agents and incorporating an adaptive update mechanism to eliminate the dependency on global topology information. Ulteriorly, by solving convex optimization problems, a distributed resilient bipartite controller relying on the observer state is formulated, and achieves the expected $mathcal {H}_{infty }$ performance while remaining resilient against replay attacks. Finally, the superiority of the proposed method is validated through comparative examples.
{"title":"Distributed $mathcal {H}_{infty }$ Resilient Bipartite Control of Multiagent Systems With Semi-Markov Switching","authors":"Lin Sun;Mingming Wang;Chong Wu;Yuan Ping;Juntong Qi","doi":"10.1109/JSYST.2024.3506812","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3506812","url":null,"abstract":"When information interaction occurs among agents, the communication network could be attacked or the signal interrupted, culminating in systemic instability and mission failure. Therefore, this article proposes <inline-formula><tex-math>$mathcal {H}_{infty }$</tex-math></inline-formula> resilient bipartite control method to address the security problem of network information interaction among agents within competitive and cooperative multiagent systems. When the communication networks among agents are subject to a replay attack, the system model integrating multisensor weight fusion with an unknown input leader is established first. Then, a detection fusion algorithm is proposed to simultaneously uncover attacker behavior and identify tampered sensors. Considering the intermittent or interrupted communication resulting from the time variability of topology switching among agents, the switching topology is modeled by a semi-Markov process within a signed graph having positive and negative interaction weights. Subsequently, a distributed observer is designed to estimate the unknown input leader, utilizing the semi-Markov interactions among agents and incorporating an adaptive update mechanism to eliminate the dependency on global topology information. Ulteriorly, by solving convex optimization problems, a distributed resilient bipartite controller relying on the observer state is formulated, and achieves the expected <inline-formula><tex-math>$mathcal {H}_{infty }$</tex-math></inline-formula> performance while remaining resilient against replay attacks. Finally, the superiority of the proposed method is validated through comparative examples.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"152-163"},"PeriodicalIF":4.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-12DOI: 10.1109/JSYST.2024.3514272
{"title":"2024 Index IEEE Systems Journal Vol. 18","authors":"","doi":"10.1109/JSYST.2024.3514272","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3514272","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"2177-2223"},"PeriodicalIF":4.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10795294","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network-assisted full-duplex (NAFD) cell-free massive multiple-input–multiple-output (MIMO) systems, which virtually achieve FD transmission by employing half-duplex access points (APs) to simultaneously serve uplink (UL) and downlink (DL) users on the same frequency bands, can decrease latency and enhance reliability since self-interference cancellation is unnecessary and macrodiversity is provided, thus helping industrial ultrareliable low-latency communication applications. In this article, we consider a monitoring scenario of industrial automation in NAFD cell-free systems using finite blocklength codewords and analyze UL and DL signals, end-to-end (E2E) delay, and E2E decoding error probability (DEP). Then, an optimization problem is formulated to minimize the maximum E2E DEP among all actuators by jointly designing AP working mode, UL and DL blocklengths under the E2E delay constraint. We propose the estimation of distribution algorithm-differential evolution (EDA-DE) method with low complexity to obtain a near-optimal solution, where the block coordinate descent is used to divide this problem into two parts. The first AP working mode selection is solved by EDA, and the second UL and DL blocklengths are designed by DE. Simulation results indicate that the performance of our proposed EDA-DE method is close to that of exhaustive search with lower computational complexity.
{"title":"AP Working Mode Selection and Blocklength Optimization for Industrial URLLC in Network-Assisted Full-Duplex Cell-Free Massive MIMO Systems","authors":"Zheng Sheng;Pengcheng Zhu;Peng Hao;Feng Shu;Fu-Chun Zheng","doi":"10.1109/JSYST.2024.3507049","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3507049","url":null,"abstract":"Network-assisted full-duplex (NAFD) cell-free massive multiple-input–multiple-output (MIMO) systems, which virtually achieve FD transmission by employing half-duplex access points (APs) to simultaneously serve uplink (UL) and downlink (DL) users on the same frequency bands, can decrease latency and enhance reliability since self-interference cancellation is unnecessary and macrodiversity is provided, thus helping industrial ultrareliable low-latency communication applications. In this article, we consider a monitoring scenario of industrial automation in NAFD cell-free systems using finite blocklength codewords and analyze UL and DL signals, end-to-end (E2E) delay, and E2E decoding error probability (DEP). Then, an optimization problem is formulated to minimize the maximum E2E DEP among all actuators by jointly designing AP working mode, UL and DL blocklengths under the E2E delay constraint. We propose the estimation of distribution algorithm-differential evolution (EDA-DE) method with low complexity to obtain a near-optimal solution, where the block coordinate descent is used to divide this problem into two parts. The first AP working mode selection is solved by EDA, and the second UL and DL blocklengths are designed by DE. Simulation results indicate that the performance of our proposed EDA-DE method is close to that of exhaustive search with lower computational complexity.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"188-199"},"PeriodicalIF":4.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-09DOI: 10.1109/JSYST.2024.3506560
Jiayi Zheng;Shulong Zhao;Xiangke Wang
This article investigates a prescribed-time method for multiple fixed-wing autonomous aerial vehicles (AAVs) to enclose and track a moving target based on relative measurements. Utilizing onboard sensors brings two main challenges, i.e., maintaining the target within the field-of-view and tracking a noncooperative target with limited information. To this end, a prescribed-time enclosing and tracking controller is proposed first, guaranteeing that multiple fixed-wing AAVs converge to the desired trajectories within a prescribed time subject to motion and visibility constraints. Then, considering the dilemma of the input saturation and prescribed-time convergence, a basis for selecting the proper prescribed time is analyzed by mathematical formulations. It is determined by different initial states and constraints rather than arbitrarily. Finally, comparison and simulation results verify the effectiveness of the proposed method within a prescribed time.
{"title":"Prescribed-Time Target Enclosing and Tracking With Motion and Visibility Constraints","authors":"Jiayi Zheng;Shulong Zhao;Xiangke Wang","doi":"10.1109/JSYST.2024.3506560","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3506560","url":null,"abstract":"This article investigates a prescribed-time method for multiple fixed-wing autonomous aerial vehicles (AAVs) to enclose and track a moving target based on relative measurements. Utilizing onboard sensors brings two main challenges, i.e., maintaining the target within the field-of-view and tracking a noncooperative target with limited information. To this end, a prescribed-time enclosing and tracking controller is proposed first, guaranteeing that multiple fixed-wing AAVs converge to the desired trajectories within a prescribed time subject to motion and visibility constraints. Then, considering the dilemma of the input saturation and prescribed-time convergence, a basis for selecting the proper prescribed time is analyzed by mathematical formulations. It is determined by different initial states and constraints rather than arbitrarily. Finally, comparison and simulation results verify the effectiveness of the proposed method within a prescribed time.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"224-233"},"PeriodicalIF":4.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1109/JSYST.2024.3486435
{"title":"IEEE Systems Council Information","authors":"","doi":"10.1109/JSYST.2024.3486435","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3486435","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"C3-C3"},"PeriodicalIF":4.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10778091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1109/JSYST.2024.3486431
{"title":"IEEE Systems Journal Publication Information","authors":"","doi":"10.1109/JSYST.2024.3486431","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3486431","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"C2-C2"},"PeriodicalIF":4.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10778090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1109/JSYST.2024.3486437
{"title":"IEEE Systems Journal Information for Authors","authors":"","doi":"10.1109/JSYST.2024.3486437","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3486437","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"C4-C4"},"PeriodicalIF":4.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10778092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-03DOI: 10.1109/JSYST.2024.3482449
Hongchao Song;Zhenlei Wang
Based on model predictive control and an attack detection mechanism, the stabilization problem of a class of nonlinear discrete-time cyber–physical systems with deception attacks at the sensor-to-controller and controller-to-actuator communication channels is studied. In this article, the deception attacks on both ends of the controller are considered using a more generic probability model. Attack detection models and mechanisms are established to detect the integrity of transmitted information in order to mitigate the impact of deception attacks. To ensure the input-to-state practical stability of the closed-loop system, a model predictive controller is designed based on the detected state. Finally, a simulation case is presented to demonstrate the stability and effectiveness of the proposed method.
{"title":"Model Predictive Control for Nonlinear Discrete Cyber–Physical Systems With Joint Deception Attacks","authors":"Hongchao Song;Zhenlei Wang","doi":"10.1109/JSYST.2024.3482449","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3482449","url":null,"abstract":"Based on model predictive control and an attack detection mechanism, the stabilization problem of a class of nonlinear discrete-time cyber–physical systems with deception attacks at the sensor-to-controller and controller-to-actuator communication channels is studied. In this article, the deception attacks on both ends of the controller are considered using a more generic probability model. Attack detection models and mechanisms are established to detect the integrity of transmitted information in order to mitigate the impact of deception attacks. To ensure the input-to-state practical stability of the closed-loop system, a model predictive controller is designed based on the detected state. Finally, a simulation case is presented to demonstrate the stability and effectiveness of the proposed method.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"20-31"},"PeriodicalIF":4.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-03DOI: 10.1109/JSYST.2024.3496754
Yuhong Zhu;Yongzhi Zhou;Yong Sun;Wei Li
Despite great progress in modeling the resilience response of power systems under extreme events, it remains difficult to assess the evolutionary trend of system performance at a specific observation moment during such events. Conventional simulation-based assessment methods are typically time-consuming because a series of scenario-specific optimization problems must be solved as a prerequisite. Thus, a spatial-temporal graph-based approach is proposed for fast resilience assessment to provide timely warning information. The key factors, including observable meteorological information, component vulnerabilities, emergency dispatch, and repair strategies, are modeled in the form of matrices that depict the spatial and temporal relationships. Based on these matrices, a spatiotemporal graph neural network is developed to fit the mapping relationship between observable states and resilience indicators, which is trained offline and enables fast assessment via forward inference. Regarding the uncertainties of various extreme scenarios, the evaluation procedure combines the whole-process simulation and single-state replay technologies, which can respectively consider the uncertainties and provide deterministic data labeling for assessment. Finally, the effectiveness of the proposed method is verified on the benchmarks, including the IEEE 118-bus system and a realistic 2868-bus system.
{"title":"Fast Resilience Assessment for Power Systems Under Typhoons Based on Spatial Temporal Graphs","authors":"Yuhong Zhu;Yongzhi Zhou;Yong Sun;Wei Li","doi":"10.1109/JSYST.2024.3496754","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3496754","url":null,"abstract":"Despite great progress in modeling the resilience response of power systems under extreme events, it remains difficult to assess the evolutionary trend of system performance at a specific observation moment during such events. Conventional simulation-based assessment methods are typically time-consuming because a series of scenario-specific optimization problems must be solved as a prerequisite. Thus, a spatial-temporal graph-based approach is proposed for fast resilience assessment to provide timely warning information. The key factors, including observable meteorological information, component vulnerabilities, emergency dispatch, and repair strategies, are modeled in the form of matrices that depict the spatial and temporal relationships. Based on these matrices, a spatiotemporal graph neural network is developed to fit the mapping relationship between observable states and resilience indicators, which is trained offline and enables fast assessment via forward inference. Regarding the uncertainties of various extreme scenarios, the evaluation procedure combines the whole-process simulation and single-state replay technologies, which can respectively consider the uncertainties and provide deterministic data labeling for assessment. Finally, the effectiveness of the proposed method is verified on the benchmarks, including the IEEE 118-bus system and a realistic 2868-bus system.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"8-19"},"PeriodicalIF":4.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we study a distributed multiscale formation optimization problem for the multiagent system. The global cost function is subjected to a constraint with an aggregative item, which reveals the degree of aggregation for the multiagent system. A distributed strategy is proposed to optimize the formation configuration at multiple scales, including the position, angle, and size of the formation configuration. The strategy first employs observation and parameter projection technologies to search for the optimal size. Then, it utilizes the gradient and moment to optimize the position and angle of the formation configuration synchronously. Finally, some simulation results are provided to verify the proposed strategy.
{"title":"Distributed Multiscale Formation Optimization for Multiagent Systems","authors":"Zhaoxia Peng;Bofan Wu;Guoguang Wen;Tingwen Huang;Ahmed Rahmani","doi":"10.1109/JSYST.2024.3502074","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3502074","url":null,"abstract":"In this article, we study a distributed multiscale formation optimization problem for the multiagent system. The global cost function is subjected to a constraint with an aggregative item, which reveals the degree of aggregation for the multiagent system. A distributed strategy is proposed to optimize the formation configuration at multiple scales, including the position, angle, and size of the formation configuration. The strategy first employs observation and parameter projection technologies to search for the optimal size. Then, it utilizes the gradient and moment to optimize the position and angle of the formation configuration synchronously. Finally, some simulation results are provided to verify the proposed strategy.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 1","pages":"339-342"},"PeriodicalIF":4.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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