Ieee-Caa Journal of Automatica Sinica最新文献_第2页

A Learning-Based Passive Resilient Controller for Cyber-Physical Systems: Countering Stealthy Deception Attacks and Complete Loss of Actuators Control Authority 一种基于学习的网络物理系统被动弹性控制器：对抗隐形欺骗攻击和执行器控制权限完全丧失

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2024.124683

Liang Xin;Zhi-Qiang Long

{"title":"A Learning-Based Passive Resilient Controller for Cyber-Physical Systems: Countering Stealthy Deception Attacks and Complete Loss of Actuators Control Authority","authors":"Liang Xin;Zhi-Qiang Long","doi":"10.1109/JAS.2024.124683","DOIUrl":"https://doi.org/10.1109/JAS.2024.124683","url":null,"abstract":"Cyber-physical systems (CPSs) are increasingly vulnerable to cyber-attacks due to their integral connection between cyberspace and the physical world, which is augmented by Internet connectivity. This vulnerability necessitates a heightened focus on developing resilient control mechanisms for CPSs. However, current observer-based active compensation resilient controllers exhibit poor performance against stealthy deception attacks (SDAs) due to the difficulty in accurately reconstructing system states because of the stealthy nature of these attacks. Moreover, some non-active compensation approaches are insufficient when there is a complete loss of actuator control authority. To address these issues, we introduce a novel learning-based passive resilient controller (LPRC). Our approach, unlike observer-based state reconstruction, shows enhanced effectiveness in countering SDAs. We developed a safety state set, represented by an ellipsoid, to ensure CPS stability under SDA conditions, maintaining system trajectories within this set. Additionally, by employing deep reinforcement learning (DRL), the LPRC acquires the capacity to adapt and diverse evolving attack strategies. To empirically substantiate our methodology, various attack methods were compared with current passive and active compensation resilient control methods to evaluate their performance.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 7","pages":"1368-1380"},"PeriodicalIF":15.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DoS Attack Schedules for Remote State Estimation in CPSs with Two-Hop Relay Networks Under Round-Robin Protocol 轮循协议下两跳中继网络cps远程状态估计的DoS攻击调度

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2024.124755

Shuo Zhang;Lei Miao;Xudong Zhao

引用次数: 0

A Robust Large-Scale Multiagent Deep Reinforcement Learning Method for Coordinated Automatic Generation Control of Integrated Energy Systems in a Performance-Based Frequency Regulation Market 基于性能的频率调节市场中集成能源系统协调自动发电控制的鲁棒大规模多智能体深度强化学习方法

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2024.124482

Jiawen Li;Tao Zhou

{"title":"A Robust Large-Scale Multiagent Deep Reinforcement Learning Method for Coordinated Automatic Generation Control of Integrated Energy Systems in a Performance-Based Frequency Regulation Market","authors":"Jiawen Li;Tao Zhou","doi":"10.1109/JAS.2024.124482","DOIUrl":"https://doi.org/10.1109/JAS.2024.124482","url":null,"abstract":"To enhance the frequency stability and lower the regulation mileage payment of a multiarea integrated energy system (IES) that supports the power Internet of Things (IoT), this paper proposes a data-driven cooperative method for automatic generation control (AGC). The method consists of adaptive fractional-order proportional-integral (FOPI) controllers and a novel efficient integration exploration multiagent twin delayed deep deterministic policy gradient (EIE-MATD3) algorithm. The FOPI controllers are designed for each area based on the performance-based frequency regulation market mechanism. The EIE-MATD3 algorithm is used to tune the coefficients of the FOPI controllers in real time using centralized training and decentralized execution. The algorithm incorporates imitation learning and efficient integration exploration to obtain a more robust coordinated control strategy. An experiment on the four-area China Southern Grid (CSG) real-time digital system shows that the proposed method can improve the control performance and reduce the regulation mileage payment of each area in the IES.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 7","pages":"1475-1488"},"PeriodicalIF":15.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

System Identification in the Network Era: A Survey of Data Issues and Innovative Approaches 网络时代的系统识别：数据问题与创新方法综述

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2024.125109

Qing-Guo Wang;Liang Zhang

{"title":"System Identification in the Network Era: A Survey of Data Issues and Innovative Approaches","authors":"Qing-Guo Wang;Liang Zhang","doi":"10.1109/JAS.2024.125109","DOIUrl":"https://doi.org/10.1109/JAS.2024.125109","url":null,"abstract":"System identification is a data-driven modeling technique that originates from the control field. It constructs models from data to mimic the behavior of dynamic systems. However, in the network era, scenarios such as sensor malfunctions, packet loss, cyber-attacks, and big data affect the quality, integrity, and security of the data. These data issues pose significant challenges to traditional system identification methods. This paper presents a comprehensive survey of the emergent challenges and advances in system identification in the network era. It explores cutting-edge methodologies to address data issues such as data loss, outliers, noise and nonlinear system identification for complex systems. To tackle the data loss, the methods based on imputation and likelihood-based inference (e.g., expectation maximization) have been employed. For outliers and noise, methods like robust regression (e.g., least median of squares, least trimmed squares) and low-rank matrix decomposition show progress in maintaining data integrity. Nonlinear system identification has advanced through kernel-based methods and neural networks, which can model complex data patterns. Finally, this paper provides valuable insights into potential directions for future research.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 7","pages":"1305-1319"},"PeriodicalIF":15.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Knowledge-Guided Self-Evolving Intelligent Behavioral Control for Autonomous Vehicles 基于知识引导的自动驾驶汽车高效自进化智能行为控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2024.124746

Qiao Peng;Kailong Liu;Jingda Wu;Amir Khajepour

引用次数: 0

Secure Consensus Control on Multi-Agent Systems Based on Improved PBFT and Raft Blockchain Consensus Algorithms 基于改进PBFT和Raft区块链共识算法的多智能体系统安全共识控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-07-01 DOI: 10.1109/JAS.2025.125300

Jing Zhu;Chengfang Lu;Juanjuan Li;Fei-Yue Wang

{"title":"Secure Consensus Control on Multi-Agent Systems Based on Improved PBFT and Raft Blockchain Consensus Algorithms","authors":"Jing Zhu;Chengfang Lu;Juanjuan Li;Fei-Yue Wang","doi":"10.1109/JAS.2025.125300","DOIUrl":"https://doi.org/10.1109/JAS.2025.125300","url":null,"abstract":"There has been significant recent research on secure control problems that arise from the open and complex real-world industrial environments. This paper focuses on addressing the issue of secure consensus control in multi-agent systems (MASs) under malicious attacks, utilizing the practical Byzantine fault tolerance (PBFT) and Raft consensus algorithm in blockchain. Unlike existing secure consensus control algorithms that have strict requirements for topology and high communication costs, our approach introduces a node grouping methodology based on system topology. Additionally, we utilize the PBFT consensus algorithm for intergroup leader identity verification, effectively reducing the communication complexity of PBFT in large-scale networks. Furthermore, we enhance the Raft algorithm through cryptographic validation during followers' log replication, which enhances the security of the system. Our proposed consensus process not only identifies the identities of malicious agents but also ensures consensus among normal agents. Through extensive simulations, we demonstrate robust convergence, particularly in scenarios with the relaxed topological requirements. Comparative experiments also validate the algorithm's lower consensus latency and improved efficiency compared to direct PBFT utilization for identity verification and classical secure consensus control method mean subsequence reduced (MSR) algorithm.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 7","pages":"1407-1417"},"PeriodicalIF":15.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Optimization Control for Cyber-Physical Systems Subject to Jamming Attack: A Nested Game Approach 受干扰攻击的网络物理系统鲁棒优化控制：一种嵌套博弈方法

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-06-16 DOI: 10.1109/JAS.2023.123873

Min Shi;Yuan Yuan

{"title":"Robust Optimization Control for Cyber-Physical Systems Subject to Jamming Attack: A Nested Game Approach","authors":"Min Shi;Yuan Yuan","doi":"10.1109/JAS.2023.123873","DOIUrl":"https://doi.org/10.1109/JAS.2023.123873","url":null,"abstract":"Dear Editor, With the advances in computing and communication technologies, the cyber-physical system (CPS), has been used in lots of industrial fields, such as the urban water cycle, internet of things, and human-cyber systems [1], [2], which has to face up to malicious cyber-attacks towards cyber communication of control commands. Specifically, jamming attack is regarded as one of the most common attacks of decreasing network performance. Game theory is widely regarded as a method of accurately describing the interaction between jamming attacker and legitimate user [3]. In the cyber layer, the signal game model has been utilized to describe the transmission between the attacker and defender [4]. However, most previous game theoretical researches are not feasible to meet the demands of industrial CPSs mainly due to the shared communication network nature. Specifically, it leads to incomplete information for players of game owing to various network-induced phenomena and employed communication protocols. In the physical layer, the secure control [5] and estimation [6] under attack detection have been studied for CPSs. However, these methods not only rely heavily on signals injection detection, but also have no access to smart attackers who launch covert attacks so that data receivers cannot observe the attack behaviour [7]. Accordingly, the motivation arising here is to tackle the nested game problem for CPSs subject to jamming attack.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 6","pages":"1286-1288"},"PeriodicalIF":15.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11036661","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}

引用次数: 0

SILIC: Intelligent On/Off Control for Networked Solar Insecticidal Lamps SILIC：联网太阳能杀虫灯的智能开/关控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-06-16 DOI: 10.1109/JAS.2024.124668

Heyang Yao;Lei Shu;Yuli Yang;Miguel Martínez-García;Wei Lin

{"title":"SILIC: Intelligent On/Off Control for Networked Solar Insecticidal Lamps","authors":"Heyang Yao;Lei Shu;Yuli Yang;Miguel Martínez-García;Wei Lin","doi":"10.1109/JAS.2024.124668","DOIUrl":"https://doi.org/10.1109/JAS.2024.124668","url":null,"abstract":"The solar insecticidal lamp (SIL) is an innovative green control device. Nevertheless, a major challenge is often encountered when carrying out insecticidal work is low energy utilization efficiency. The substantial energy consumption required to turn on the SIL, coupled with the extension of insecticidal working time during the low pest activity periods, can result in low energy efficiency. Especially when the energy storage level is below 50%, the inefficient use of energy significantly reduces the effectiveness of pest control. Consequently, an ineffective on/off scheme for these lamps may lead to suboptimal energy utilization. In this paper, we present the solar insecticidal lamp intelligent energy management scheme (SIL-IEMS) to address the challenge of inefficient energy utilization in the solar insecticidal lamp internet of things (SIL-IoT). SIL-IEMS primarily utilizes genetic algorithm (GA) and greedy algorithms to optimize insecticidal working time by considering constraints such as residual energy and the number of trap pests. Comparing SIL-IEMS to the traditional remote switching method (TRSM) and the solar insecticidal lamp genetic algorithm (SILGA), our simulation results showcase its superior energy efficiency and pest control effectiveness. Particularly noteworthy is the SILIEMS's 17.6% increase in insecticidal efficiency compared to TRSM and 6% improvement over SILGA when the SIL begins with a remaining energy level of 15%.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 6","pages":"1221-1235"},"PeriodicalIF":15.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Embodied Multi-Agent Systems: A Review 嵌入式多智能体系统：综述

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-06-16 DOI: 10.1109/JAS.2025.125552

Zhuo Li;Weiran Wu;Yunlong Guo;Jian Sun;Qing-Long Han

{"title":"Embodied Multi-Agent Systems: A Review","authors":"Zhuo Li;Weiran Wu;Yunlong Guo;Jian Sun;Qing-Long Han","doi":"10.1109/JAS.2025.125552","DOIUrl":"https://doi.org/10.1109/JAS.2025.125552","url":null,"abstract":"Multi-agent systems (MASs) have demonstrated significant achievements in a wide range of tasks, leveraging their capacity for coordination and adaptation within complex environments. Moreover, the enhancement of their intelligent functionalities is crucial for tackling increasingly challenging tasks. This goal resonates with a paradigm shift within the artificial intelligence (AI) community, from “internet AI” to “embodied AI”, and the MASs with embodied AI are referred to as embodied multi-agent systems (EMASs). An EMAS has the potential to acquire generalized competencies through interactions with environments, enabling it to effectively address a variety of tasks and thereby make a substantial contribution to the quest for artificial general intelligence. Despite the burgeoning interest in this domain, a comprehensive review of EMAS has been lacking. This paper offers analysis and synthesis for EMASs from a control perspective, conceptualizing each embodied agent as an entity equipped with a “brain” for decision and a “body” for environmental interaction. System designs are classified into open-loop, closed-loop, and double-loop categories, and EMAS implementations are discussed. Additionally, the current applications and challenges faced by EMASs are summarized and potential avenues for future research in this field are provided.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 6","pages":"1095-1116"},"PeriodicalIF":15.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bearings-Only Target Motion Analysis via Deep Reinforcement Learning 基于深度强化学习的方位目标运动分析

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-06-16 DOI: 10.1109/JAS.2024.124449

Chengyi Zhou;Meiqin Liu;Senlin Zhang;Ronghao Zheng;Shanling Dong

引用次数: 0