Pub Date : 2024-09-11DOI: 10.1109/JSYST.2024.3423489
Miaomiao Ma;Jing Cui;Xiangjie Liu;Kwang Y. Lee
This article considers the distributed economic model predictive control (DEMPC) scheme for addressing the load frequency control problem in a multiarea interconnected power system with wind turbines. The system is divided into multiple dynamically coupled subsystems, each subjected to state and control input constraints due to safety concerns. The overall optimal control problem is decomposed into several local optimal control problems based on the local information of each subsystem, meaning each area designs its own local DEMPC controller. Within this framework, the future state trajectories of neighboring subsystems are estimated from the transmitted information between neighbors. To enhance overall economic benefits, the economic stage cost, including load frequency regulation cost, fuel consumption cost, and wind generation cost, is incorporated into the cost function. Simulation results and analysis under different scenarios demonstrate potential improvements in computational burden, economic performance, and robustness of the designed DEMPC controller.
{"title":"Distributed Economic Model Predictive Load Frequency Control for the Multiarea Interconnected Power System With WTs","authors":"Miaomiao Ma;Jing Cui;Xiangjie Liu;Kwang Y. Lee","doi":"10.1109/JSYST.2024.3423489","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3423489","url":null,"abstract":"This article considers the distributed economic model predictive control (DEMPC) scheme for addressing the load frequency control problem in a multiarea interconnected power system with wind turbines. The system is divided into multiple dynamically coupled subsystems, each subjected to state and control input constraints due to safety concerns. The overall optimal control problem is decomposed into several local optimal control problems based on the local information of each subsystem, meaning each area designs its own local DEMPC controller. Within this framework, the future state trajectories of neighboring subsystems are estimated from the transmitted information between neighbors. To enhance overall economic benefits, the economic stage cost, including load frequency regulation cost, fuel consumption cost, and wind generation cost, is incorporated into the cost function. Simulation results and analysis under different scenarios demonstrate potential improvements in computational burden, economic performance, and robustness of the designed DEMPC controller.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"1629-1638"},"PeriodicalIF":4.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169632","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 : 2024-09-11DOI: 10.1109/JSYST.2024.3428031
{"title":"IEEE Systems Journal Information for Authors","authors":"","doi":"10.1109/JSYST.2024.3428031","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3428031","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"C4-C4"},"PeriodicalIF":4.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10678820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169630","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 : 2024-09-11DOI: 10.1109/JSYST.2024.3427905
{"title":"IEEE Systems Journal Publication Information","authors":"","doi":"10.1109/JSYST.2024.3427905","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3427905","url":null,"abstract":"","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"C2-C2"},"PeriodicalIF":4.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10678797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169607","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 : 2024-09-09DOI: 10.1109/JSYST.2024.3446825
Mohamed Ramadan Younis;Reza Iravani
This article proposes a novel hybrid time-domain and direct stability method for rotor-angle stability assessment, aiming to improve the efficiency of existing approaches. The proposed method enables faster detection of both small-signal and transient stability scenarios while extending the applications of the classical stability direct methods to multiswing stability analysis. Unlike the conventional direct methods that rely on the overall system energy, the proposed approach calculates the system's critical energy using the critical apparatus energies, facilitating multiswing stability analysis. Key contributions of this work include the introduction of a new metric, termed “the time to instability,” which allows for the prediction of separation or islanding areas during disturbances. Additionally, the proposed method can rank all apparatus in a power system based on their criticality during small or large disturbances. Also, a stopping condition for the time-domain simulation is provided, reducing algorithm execution time and rendering it suitable for real-time or near-real-time application of dynamic security assessment. The proposed method is tested with multiple stability scenarios and the four possible stability scenarios are presented in this article using the IEEE 16-machine 68-bus power system. The results demonstrate the high accuracy of the proposed approach in identifying the critical apparatus and assessing first- and multirotor-anglestability in power systems.
{"title":"A Hybrid Method for Fast Rotor-Angle Stability Assessment","authors":"Mohamed Ramadan Younis;Reza Iravani","doi":"10.1109/JSYST.2024.3446825","DOIUrl":"10.1109/JSYST.2024.3446825","url":null,"abstract":"This article proposes a novel hybrid time-domain and direct stability method for rotor-angle stability assessment, aiming to improve the efficiency of existing approaches. The proposed method enables faster detection of both small-signal and transient stability scenarios while extending the applications of the classical stability direct methods to multiswing stability analysis. Unlike the conventional direct methods that rely on the overall system energy, the proposed approach calculates the system's critical energy using the critical apparatus energies, facilitating multiswing stability analysis. Key contributions of this work include the introduction of a new metric, termed “the time to instability,” which allows for the prediction of separation or islanding areas during disturbances. Additionally, the proposed method can rank all apparatus in a power system based on their criticality during small or large disturbances. Also, a stopping condition for the time-domain simulation is provided, reducing algorithm execution time and rendering it suitable for real-time or near-real-time application of dynamic security assessment. The proposed method is tested with multiple stability scenarios and the four possible stability scenarios are presented in this article using the IEEE 16-machine 68-bus power system. The results demonstrate the high accuracy of the proposed approach in identifying the critical apparatus and assessing first- and multirotor-anglestability in power systems.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"2042-2051"},"PeriodicalIF":4.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223846","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 : 2024-09-09DOI: 10.1109/JSYST.2024.3445377
Fei Zhang;Xingling Shao;Wendong Zhang
This article studies a global positioning system (GPS)-free distributed localization problem for a nonstationary target using a cluster of unmanned aerial vehicles (UAVs) loaded with bearing sensors, which aims to cooperatively estimate the relative positions of target by local interactions, regardless of whether or not the target can be directly detected. First, for leader UAVs that can readily detect the target, a novel bearing-based estimator devised in a local frame is proposed by following a prediction and correction configuration, while a sufficient condition is established to assure the asymptotic decaying of position estimation error. Second, considering follower UAVs that cannot directly observe the target, a special consensus-based cooperative fusion algorithm comprised of coupled observation and localization subsystems is proposed for UAVs to synchronize the target estimation with neighbors’ localization, wherein a fixed-time distributed observer is delicately constructed to provide target speed estimates, such that the requirements on the global availability of target speed can be avoided. The remarkable merit is that without resorting to GPS, all members can reach an agreement on relative positioning estimates in a distributed execution sense. Lyapunov approach certifies that all errors can exponentially approximate to the origin. Simulations confirm the efficacy of the presented algorithm.
{"title":"Cooperative Fusion Localization of a Nonstationary Target for Multiple UAVs Without GPS","authors":"Fei Zhang;Xingling Shao;Wendong Zhang","doi":"10.1109/JSYST.2024.3445377","DOIUrl":"10.1109/JSYST.2024.3445377","url":null,"abstract":"This article studies a global positioning system (GPS)-free distributed localization problem for a nonstationary target using a cluster of unmanned aerial vehicles (UAVs) loaded with bearing sensors, which aims to cooperatively estimate the relative positions of target by local interactions, regardless of whether or not the target can be directly detected. First, for leader UAVs that can readily detect the target, a novel bearing-based estimator devised in a local frame is proposed by following a prediction and correction configuration, while a sufficient condition is established to assure the asymptotic decaying of position estimation error. Second, considering follower UAVs that cannot directly observe the target, a special consensus-based cooperative fusion algorithm comprised of coupled observation and localization subsystems is proposed for UAVs to synchronize the target estimation with neighbors’ localization, wherein a fixed-time distributed observer is delicately constructed to provide target speed estimates, such that the requirements on the global availability of target speed can be avoided. The remarkable merit is that without resorting to GPS, all members can reach an agreement on relative positioning estimates in a distributed execution sense. Lyapunov approach certifies that all errors can exponentially approximate to the origin. Simulations confirm the efficacy of the presented algorithm.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"1951-1962"},"PeriodicalIF":4.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183240","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 : 2024-09-06DOI: 10.1109/JSYST.2024.3450883
Wenjiang Ouyang;Qian Liu;Junsheng Mu;Anwer AI-Dulaimi;Xiaojun Jing;Qilie Liu
Integrated sensing and communication (ISAC) has attracted great attention with the gains of spectrum efficiency and deployment costs through the coexistence of sensing and communication functions. Meanwhile, federated learning (FL) has great potential to apply to large-scale multiagent systems (LSMAS) in ISAC due to the attractive privacy protection mechanism. Nonindependent identically distribution (non-IID) is a fundamental challenge in FL and seriously affects the convergence performance. To deal with the non-IID issue in FL, a data augmentation optimization algorithm (DAOA) is proposed based on reinforcement learning (RL), where an augmented dataset is generated based on a generative adversarial network (GAN) and the local model parameters are inputted into a deep Q-network (DQN) to learn the optimal number of augmented data. Different from the existing works that only optimize the training performance, the number of augmented data is also considered to improve the sample efficiency in the article. In addition, to alleviate the high-dimensional input challenge in DQN and reduce the communication overhead in FL, a lightweight model is applied to the client based on deep separable convolution (DSC). Simulation results indicate that our proposed DAOA algorithm acquires considerable performance with significantly fewer augmented data, and the communication overhead is reduced greatly compared with benchmark algorithms.
{"title":"Communication-Efficient Federated Learning for Large-Scale Multiagent Systems in ISAC: Data Augmentation With Reinforcement Learning","authors":"Wenjiang Ouyang;Qian Liu;Junsheng Mu;Anwer AI-Dulaimi;Xiaojun Jing;Qilie Liu","doi":"10.1109/JSYST.2024.3450883","DOIUrl":"10.1109/JSYST.2024.3450883","url":null,"abstract":"Integrated sensing and communication (ISAC) has attracted great attention with the gains of spectrum efficiency and deployment costs through the coexistence of sensing and communication functions. Meanwhile, federated learning (FL) has great potential to apply to large-scale multiagent systems (LSMAS) in ISAC due to the attractive privacy protection mechanism. Nonindependent identically distribution (non-IID) is a fundamental challenge in FL and seriously affects the convergence performance. To deal with the non-IID issue in FL, a data augmentation optimization algorithm (DAOA) is proposed based on reinforcement learning (RL), where an augmented dataset is generated based on a generative adversarial network (GAN) and the local model parameters are inputted into a deep Q-network (DQN) to learn the optimal number of augmented data. Different from the existing works that only optimize the training performance, the number of augmented data is also considered to improve the sample efficiency in the article. In addition, to alleviate the high-dimensional input challenge in DQN and reduce the communication overhead in FL, a lightweight model is applied to the client based on deep separable convolution (DSC). Simulation results indicate that our proposed DAOA algorithm acquires considerable performance with significantly fewer augmented data, and the communication overhead is reduced greatly compared with benchmark algorithms.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"1893-1904"},"PeriodicalIF":4.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223845","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 : 2024-09-05DOI: 10.1109/JSYST.2024.3423012
Huifang Li;Jing Li;Meng Liu;Fengkui Gong
In this article, we investigate the physical layer security for a relay-aided multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) system, where an eavesdropper tries to intercept confidential information transmission from the source and the relay by employing selection combining and maximal ratio combining, respectively. Specifically, we propose an optimal transmit antenna selection scheme to exploit the inherent spatial diversity gain for security enhancement. The closed-form expressions for the secrecy outage probability are derived to facilitate the system performance evaluation. At a more pragmatic level, we consider multiple users in the relay-aided MISO NOMA system and thus propose a user pairing algorithm to perfect successive interference cancellation. The algorithm avoids full search over all users by exploiting two-sided matching and low-complexity greed, thereby reducing the total complexity. Furthermore, aiming to maximize the secrecy rate, we formulate an optimization problem. Hence, the power allocation schemes are developed by jointly considering power limits and rate requirements. The scheme achieves closed-form solutions of power allocation for the data rate requirements of each user. Finally, simulation results validate the accuracy of the derived analysis and the improvement significant in secrecy performance by the proposed algorithm and scheme.
{"title":"Performance Analysis and Secure Resource Allocation for Relay-Aided MISO-NOMA Systems","authors":"Huifang Li;Jing Li;Meng Liu;Fengkui Gong","doi":"10.1109/JSYST.2024.3423012","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3423012","url":null,"abstract":"In this article, we investigate the physical layer security for a relay-aided multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) system, where an eavesdropper tries to intercept confidential information transmission from the source and the relay by employing selection combining and maximal ratio combining, respectively. Specifically, we propose an optimal transmit antenna selection scheme to exploit the inherent spatial diversity gain for security enhancement. The closed-form expressions for the secrecy outage probability are derived to facilitate the system performance evaluation. At a more pragmatic level, we consider multiple users in the relay-aided MISO NOMA system and thus propose a user pairing algorithm to perfect successive interference cancellation. The algorithm avoids full search over all users by exploiting two-sided matching and low-complexity greed, thereby reducing the total complexity. Furthermore, aiming to maximize the secrecy rate, we formulate an optimization problem. Hence, the power allocation schemes are developed by jointly considering power limits and rate requirements. The scheme achieves closed-form solutions of power allocation for the data rate requirements of each user. Finally, simulation results validate the accuracy of the derived analysis and the improvement significant in secrecy performance by the proposed algorithm and scheme.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"1617-1628"},"PeriodicalIF":4.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169633","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 : 2024-09-05DOI: 10.1109/JSYST.2024.3412985
Xuguang Hu;Junkai Zhang;Dazhong Ma;Qingchen Wang;Qiuye Sun
With the active participation of numerous end-users in the development of low-carbon energy ecosystems, the continuous expansion of the Energy Internet diminishes the timeliness of energy transmission and increases the complexity of energy scheduling, which leads to reduced energy efficiency. To solve it, a partitioning approach based on dual-stage agglomeration for Energy Internet is proposed in this article. First, the entropy weight of Energy Internet is proposed to assess the line significance of energy transmission, while establishing a uniform criterion of judgment by considering the energy loss of heterogeneous energy sources. Second, as the first stage of partitioning, the local expansion and boundary detection mechanism is proposed to realize localized node agglomeration and generate small-scale regions while ensuring all nodes contained in subregions. Furthermore, the hierarchical region agglomeration mechanism is proposed as the second stage of partitioning, which can aggregate the generated small-scale regions and improve the quality of the partitioning result based on flexible partitioning. Through the above stages, the proposed partitioning approach improves energy allocation, transmission and global efficiency of Energy Internet. Finally, case studies of an Energy Internet with 171-node are presented to validate the proposed approach.
{"title":"Dual-Stage Agglomeration Strategy: An Approach of Flexible Partitioning for Energy Internet","authors":"Xuguang Hu;Junkai Zhang;Dazhong Ma;Qingchen Wang;Qiuye Sun","doi":"10.1109/JSYST.2024.3412985","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3412985","url":null,"abstract":"With the active participation of numerous end-users in the development of low-carbon energy ecosystems, the continuous expansion of the Energy Internet diminishes the timeliness of energy transmission and increases the complexity of energy scheduling, which leads to reduced energy efficiency. To solve it, a partitioning approach based on dual-stage agglomeration for Energy Internet is proposed in this article. First, the entropy weight of Energy Internet is proposed to assess the line significance of energy transmission, while establishing a uniform criterion of judgment by considering the energy loss of heterogeneous energy sources. Second, as the first stage of partitioning, the local expansion and boundary detection mechanism is proposed to realize localized node agglomeration and generate small-scale regions while ensuring all nodes contained in subregions. Furthermore, the hierarchical region agglomeration mechanism is proposed as the second stage of partitioning, which can aggregate the generated small-scale regions and improve the quality of the partitioning result based on flexible partitioning. Through the above stages, the proposed partitioning approach improves energy allocation, transmission and global efficiency of Energy Internet. Finally, case studies of an Energy Internet with 171-node are presented to validate the proposed approach.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"1560-1569"},"PeriodicalIF":4.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169669","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}
With the advancement of edge computing, more and more intelligent applications are being deployed at the edge in proximity to end devices to provide in-vehicle services. However, the implementation of some complex services requires the collaboration of multiple AI models to handle and analyze various types of sensory data. In this context, the simultaneous scheduling and execution of multiple model inference tasks is an emerging scenario and faces many challenges. One of the major challenges is to reduce the completion time of time-sensitive services. In order to solve this problem, a multiagent reinforcement learning-based multimodel inference task scheduling method was proposed in this article, with a newly designed reward function to jointly optimize the overall running time and load imbalance. First, the multiagent proximal policy optimization algorithm is utilized for designing the task scheduling method. Second, the designed method can generate near-optimal task scheduling decisions and then dynamically allocate inference tasks to different edge applications based on their status and task characteristics. Third, one assessment index, quality of method, is defined and the proposed method is compared with the other five benchmark methods. Experimental results reveal that the proposed method can reduce the running time of multimodel inference by at least 25% or more, closing to the optimal solution.
{"title":"Multiagent Reinforcement Learning-Based Multimodel Running Latency Optimization in Vehicular Edge Computing Paradigm","authors":"Peisong Li;Ziren Xiao;Xinheng Wang;Muddesar Iqbal;Pablo Casaseca-de-la-Higuera","doi":"10.1109/JSYST.2024.3407213","DOIUrl":"10.1109/JSYST.2024.3407213","url":null,"abstract":"With the advancement of edge computing, more and more intelligent applications are being deployed at the edge in proximity to end devices to provide in-vehicle services. However, the implementation of some complex services requires the collaboration of multiple AI models to handle and analyze various types of sensory data. In this context, the simultaneous scheduling and execution of multiple model inference tasks is an emerging scenario and faces many challenges. One of the major challenges is to reduce the completion time of time-sensitive services. In order to solve this problem, a multiagent reinforcement learning-based multimodel inference task scheduling method was proposed in this article, with a newly designed reward function to jointly optimize the overall running time and load imbalance. First, the multiagent proximal policy optimization algorithm is utilized for designing the task scheduling method. Second, the designed method can generate near-optimal task scheduling decisions and then dynamically allocate inference tasks to different edge applications based on their status and task characteristics. Third, one assessment index, quality of method, is defined and the proposed method is compared with the other five benchmark methods. Experimental results reveal that the proposed method can reduce the running time of multimodel inference by at least 25% or more, closing to the optimal solution.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 4","pages":"1860-1870"},"PeriodicalIF":4.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183241","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 : 2024-09-02DOI: 10.1109/JSYST.2024.3408607
Lihong Feng;Bonan Huang;Xiangpeng Xie
This article investigates the output containment problem for nonlinear heterogeneous multiagent systems subjected to actuator faults. The dynamics of followers are modeled by Takagi–Sugeno (T–S) fuzzy systems, these models are effective in handling a wide range of nonlinearities. First, to address the challenge of limited information interaction between followers and leaders, a distributed compensator is developed to estimate the convex hull information derived from the leaders' states. Furthermore, a dynamic event-triggered mechanism combined with a sampler is employed to eliminate unnecessary continuous transmission, thereby reducing the communication burden and saving energy. Subsequently, fuzzy controllers are devised for the followers based on the output information and the states of compensators, ensuring the output containment of the T–S fuzzy system and preventing the propagation of actuator faults. The Lyapunov stability theory is utilized to derive rigorous convergence conditions for the system, and then, gain matrices are obtained in terms of linear matrix inequalities. A numerical simulation and a tunnel diode network circuit model simulation are provided to demonstrate the effectiveness and superiority of the proposed controller.
{"title":"Dynamic Event-Triggered Containment Control for T–S Fuzzy Multiagent Systems With Actuator Faults","authors":"Lihong Feng;Bonan Huang;Xiangpeng Xie","doi":"10.1109/JSYST.2024.3408607","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3408607","url":null,"abstract":"This article investigates the output containment problem for nonlinear heterogeneous multiagent systems subjected to actuator faults. The dynamics of followers are modeled by Takagi–Sugeno (T–S) fuzzy systems, these models are effective in handling a wide range of nonlinearities. First, to address the challenge of limited information interaction between followers and leaders, a distributed compensator is developed to estimate the convex hull information derived from the leaders' states. Furthermore, a dynamic event-triggered mechanism combined with a sampler is employed to eliminate unnecessary continuous transmission, thereby reducing the communication burden and saving energy. Subsequently, fuzzy controllers are devised for the followers based on the output information and the states of compensators, ensuring the output containment of the T–S fuzzy system and preventing the propagation of actuator faults. The Lyapunov stability theory is utilized to derive rigorous convergence conditions for the system, and then, gain matrices are obtained in terms of linear matrix inequalities. A numerical simulation and a tunnel diode network circuit model simulation are provided to demonstrate the effectiveness and superiority of the proposed controller.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 3","pages":"1538-1548"},"PeriodicalIF":4.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169661","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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