Pub Date : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107551
Zhibin Hu, Tana Guo
In this paper, the distributed resilient fusion (DRF) filter is designed for a kind of multi-sensor (MS) nonlinear singular systems with colored measurement noises. The measurement differencing way is used to deal with the colored measurement noises, ensuring that the noises of the measurement output are uncorrelated. During the algorithm implementation, the resilience case that the local filter gain is designed with the certain gain variations is considered, thereby enhancing the system robustness. In this case, our goal is that by using the full-order transformation method, the nonlinear singular system is transformed into an equivalent nonlinear nonsingular one. In addition, the DRF filtering approach is developed in terms of the inverse covariance intersection fusion method, where the local upper bound on the filtering error covariance is deduced and minimized by solving two difference equations and designing the appropriate filter gain, respectively. In the end, the effectiveness of the proposed DRF filtering algorithm is checked by using two numerical examples.
{"title":"Distributed resilient fusion filtering for multi-sensor nonlinear singular systems subject to colored measurement noises","authors":"Zhibin Hu, Tana Guo","doi":"10.1016/j.jfranklin.2025.107551","DOIUrl":"10.1016/j.jfranklin.2025.107551","url":null,"abstract":"<div><div>In this paper, the distributed resilient fusion (DRF) filter is designed for a kind of multi-sensor (MS) nonlinear singular systems with colored measurement noises. The measurement differencing way is used to deal with the colored measurement noises, ensuring that the noises of the measurement output are uncorrelated. During the algorithm implementation, the resilience case that the local filter gain is designed with the certain gain variations is considered, thereby enhancing the system robustness. In this case, our goal is that by using the full-order transformation method, the nonlinear singular system is transformed into an equivalent nonlinear nonsingular one. In addition, the DRF filtering approach is developed in terms of the inverse covariance intersection fusion method, where the local upper bound on the filtering error covariance is deduced and minimized by solving two difference equations and designing the appropriate filter gain, respectively. In the end, the effectiveness of the proposed DRF filtering algorithm is checked by using two numerical examples.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107551"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145431","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107523
Yu-Fa Liu , Dong Wang , Zhuo Wang , Ante Su , Yong-Hua Liu , Chun-Yi Su
This study addresses the problem of adaptive locally weighted learning (LWL) tracking control for a class of n-order unknown strict-feedback nonlinear systems (SFNSs). Without involving a priori information on the system dynamics, an adaptive tracking control algorithm is designed by fusing LWL and the technique of backstepping, in which the LWL is employed to identify the unknown nonlinear functions. Particularly, by introducing a novel weighting function with sufficient differentiability, the obstacle of the integration of LWL and backstepping to control SFNSs is successfully circumvented. The developed adaptive LWL tracking control scheme ensures that all closed-loop signals are bounded. Finally, simulation results are performed to testify the effectiveness of the proposed LWL tracking control approach.
{"title":"Adaptive locally weighted learning tracking control for a class of unknown strict-feedback nonlinear systems via differentiable higher order kernels","authors":"Yu-Fa Liu , Dong Wang , Zhuo Wang , Ante Su , Yong-Hua Liu , Chun-Yi Su","doi":"10.1016/j.jfranklin.2025.107523","DOIUrl":"10.1016/j.jfranklin.2025.107523","url":null,"abstract":"<div><div>This study addresses the problem of adaptive locally weighted learning (LWL) tracking control for a class of n-order unknown strict-feedback nonlinear systems (SFNSs). Without involving a priori information on the system dynamics, an adaptive tracking control algorithm is designed by fusing LWL and the technique of backstepping, in which the LWL is employed to identify the unknown nonlinear functions. Particularly, by introducing a novel weighting function with sufficient differentiability, the obstacle of the integration of LWL and backstepping to control SFNSs is successfully circumvented. The developed adaptive LWL tracking control scheme ensures that all closed-loop signals are bounded. Finally, simulation results are performed to testify the effectiveness of the proposed LWL tracking control approach.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107523"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146027","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107533
Shikun Zhang, Dan Liu, Xiaohong Cui, Kun Zhou, Binrui Wang
This paper aims to study the finite-time (FNT) and fixed-time (FXT) cluster synchronization problems of complex networks (CNs). First, to ensure scalability of CNs, the adaptive laws are proposed to update coupling weights between neighboring nodes in same cluster. In this case, only local information is required instead of global one. Then, by designing the appropriate controllers and employing Lyapunov stable theory, several sufficient conditions are obtained to fulfill cluster synchronization in FNT and FXT. When the number of clusters is single, the general FNT and FXT synchronization are also investigated under distributed adaptive strategies. Finally, the theoretical results are verified by a numerical simulation example.
{"title":"Distributed adaptive finite-time and fixed-time cluster synchronization of complex networks","authors":"Shikun Zhang, Dan Liu, Xiaohong Cui, Kun Zhou, Binrui Wang","doi":"10.1016/j.jfranklin.2025.107533","DOIUrl":"10.1016/j.jfranklin.2025.107533","url":null,"abstract":"<div><div>This paper aims to study the finite-time (FNT) and fixed-time (FXT) cluster synchronization problems of complex networks (CNs). First, to ensure scalability of CNs, the adaptive laws are proposed to update coupling weights between neighboring nodes in same cluster. In this case, only local information is required instead of global one. Then, by designing the appropriate controllers and employing Lyapunov stable theory, several sufficient conditions are obtained to fulfill cluster synchronization in FNT and FXT. When the number of clusters is single, the general FNT and FXT synchronization are also investigated under distributed adaptive strategies. Finally, the theoretical results are verified by a numerical simulation example.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 3","pages":"Article 107533"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137144","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2024.107424
Yinhe Li , Jinchang Ren , Hang Fu , Genyun Sun
As an essential task to identify anomalies and monitor changes over time, change detection enables detailed earth observation in remote sensing. By combining both the rich spectral information and spatial image, hyperspectral images (HSI) have offered unique and significant advantages for change detection. However, traditional hyperspectral change detection (HCD) methods, predominantly based on convolutional neural networks (CNNs), struggle with capturing long-range spatial-spectral dependencies due to their limited receptive fields. Whilst transformers based HCD methods are capable of modeling such dependencies, they often suffer from quadratic growth of the computational complexity. Considering the unique capabilities in offering robust long-range sequence modeling yet with linear computational complexity, the emerging Mamba model has provided a promising alternative. Accordingly, we propose a novel approach that integrates the global attention (GA) and state space model (SSM) to form our GASSM network for HCD. The SSM based Mamba block has been introduced to model global spatial-spectral features, followed by a fully connected layer to perform binary classification of detected changes. To the best of our knowledge, this is the first to explore using the Mamba and SSM for HCD. Comprehensive experiments on two publicly available datasets, compared with eight state-of-the-art benchmarks, have validated the efficacy and efficiency of our GASSM model, demonstrating its superiority of high accuracy and stability in HCD.
{"title":"GASSM: Global attention and state space model based end-to-end hyperspectral change detection","authors":"Yinhe Li , Jinchang Ren , Hang Fu , Genyun Sun","doi":"10.1016/j.jfranklin.2024.107424","DOIUrl":"10.1016/j.jfranklin.2024.107424","url":null,"abstract":"<div><div>As an essential task to identify anomalies and monitor changes over time, change detection enables detailed earth observation in remote sensing. By combining both the rich spectral information and spatial image, hyperspectral images (HSI) have offered unique and significant advantages for change detection. However, traditional hyperspectral change detection (HCD) methods, predominantly based on convolutional neural networks (CNNs), struggle with capturing long-range spatial-spectral dependencies due to their limited receptive fields. Whilst transformers based HCD methods are capable of modeling such dependencies, they often suffer from quadratic growth of the computational complexity. Considering the unique capabilities in offering robust long-range sequence modeling yet with linear computational complexity, the emerging Mamba model has provided a promising alternative. Accordingly, we propose a novel approach that integrates the global attention (GA) and state space model (SSM) to form our GASSM network for HCD. The SSM based Mamba block has been introduced to model global spatial-spectral features, followed by a fully connected layer to perform binary classification of detected changes. To the best of our knowledge, this is the first to explore using the Mamba and SSM for HCD. Comprehensive experiments on two publicly available datasets, compared with eight state-of-the-art benchmarks, have validated the efficacy and efficiency of our GASSM model, demonstrating its superiority of high accuracy and stability in HCD.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 3","pages":"Article 107424"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137202","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107552
Cheng Luo , Haibo Bao , Jinde Cao
This paper focuses on synchronization issue of dynamic memristor-delayed cellular neural networks (DM-DCNNs) for the first time. Different from the traditional memristor-based NNs (MNNs) that are modeled by discontinuous switched systems, DM-DCNNs where the memristor has flux-controlled and continuous-time nonlinear relation have been paid widespread attention. In order to reduce network burden, a novel memory-based event-triggered mechanism (METM) is proposed to synchronize drive–response systems of DM-DCNNs. With the help of some inequality techniques and Lyapunov stability theory, the sufficient conditions for synchronization are given by some linear matrix inequalities (LMIs). Unlike previous researches, all synchronization results were conducted in the flux-charge domain, which may be a potential advantage for information processing. Then, a numerical example is employed for supporting correctness of these synchronization criteria. Furthermore, the synchronization of DM-DCNNs under METM is further designed as a new type of encryption and decryption algorithms for image protection. Finally, the experimental performances are also provided to verify the high security of designed algorithm with anti-attack capability.
{"title":"Memory-based event-triggered synchronization of dynamic memristor delayed cellular neural networks for image encryption","authors":"Cheng Luo , Haibo Bao , Jinde Cao","doi":"10.1016/j.jfranklin.2025.107552","DOIUrl":"10.1016/j.jfranklin.2025.107552","url":null,"abstract":"<div><div>This paper focuses on synchronization issue of dynamic memristor-delayed cellular neural networks (DM-DCNNs) for the first time. Different from the traditional memristor-based NNs (MNNs) that are modeled by discontinuous switched systems, DM-DCNNs where the memristor has flux-controlled and continuous-time nonlinear relation have been paid widespread attention. In order to reduce network burden, a novel memory-based event-triggered mechanism (METM) is proposed to synchronize drive–response systems of DM-DCNNs. With the help of some inequality techniques and Lyapunov stability theory, the sufficient conditions for synchronization are given by some linear matrix inequalities (LMIs). Unlike previous researches, all synchronization results were conducted in the flux-charge domain, which may be a potential advantage for information processing. Then, a numerical example is employed for supporting correctness of these synchronization criteria. Furthermore, the synchronization of DM-DCNNs under METM is further designed as a new type of encryption and decryption algorithms for image protection. Finally, the experimental performances are also provided to verify the high security of designed algorithm with anti-attack capability.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107552"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145041","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107525
Guowei Zhao , Zhiguang Feng , Qingxiang Wang , Zhengyi Jiang , Hong Lin
In this paper, the design problem of real-time reachable set controller for singular Markov jump systems with mixed delay and parameter uncertainties is studied. Firstly, by designing a P-D controller, the system is transformed into a nonsingular mixed time-delay Markov jump system with uncertain parameters. Secondly, the sufficient conditions for the system state constraints on a bounded set are obtained through the utilization of Lyapunov functional and a free weight matrix, and the controller parameters are then determined. Finally, an example of DC motor drive system and a numerical example are given to verify the validity of the results.
{"title":"Real-time reachable set control for singular Markov jump systems with mixed delay and uncertain parameters","authors":"Guowei Zhao , Zhiguang Feng , Qingxiang Wang , Zhengyi Jiang , Hong Lin","doi":"10.1016/j.jfranklin.2025.107525","DOIUrl":"10.1016/j.jfranklin.2025.107525","url":null,"abstract":"<div><div>In this paper, the design problem of real-time reachable set controller for singular Markov jump systems with mixed delay and parameter uncertainties is studied. Firstly, by designing a P-D controller, the system is transformed into a nonsingular mixed time-delay Markov jump system with uncertain parameters. Secondly, the sufficient conditions for the system state constraints on a bounded set are obtained through the utilization of Lyapunov functional and a free weight matrix, and the controller parameters are then determined. Finally, an example of DC motor drive system and a numerical example are given to verify the validity of the results.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107525"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378977","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107569
Cheng Tan , Binlian Zhu , Ziran Chen , Wing Shing Wong
This paper addresses the indefinite linear quadratic (LQ) optimal control problem within mean-field stochastic systems characterized by asymmetric information. In such models, multiple controllers operate, each with a unique information structure. Notably, the introduction of mean-field terms disrupts the adaptiveness of control inputs, thereby making the control problem under consideration distinct from the standard LQ formulations. Employing the maximum principle, we propose necessary and sufficient conditions for the indefinite LQ control problem by considering forward and backward stochastic difference equations (FBSDEs). Specifically, through an orthogonal decomposition method, we introduce a novel technique to decouple the FBSDEs, facilitating the derivation of optimal controllers via non-symmetric Riccati equations. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.
{"title":"Indefinite LQ optimal control for mean-field stochastic systems with information asymmetry","authors":"Cheng Tan , Binlian Zhu , Ziran Chen , Wing Shing Wong","doi":"10.1016/j.jfranklin.2025.107569","DOIUrl":"10.1016/j.jfranklin.2025.107569","url":null,"abstract":"<div><div>This paper addresses the indefinite linear quadratic (LQ) optimal control problem within mean-field stochastic systems characterized by asymmetric information. In such models, multiple controllers operate, each with a unique information structure. Notably, the introduction of mean-field terms disrupts the adaptiveness of control inputs, thereby making the control problem under consideration distinct from the standard LQ formulations. Employing the maximum principle, we propose necessary and sufficient conditions for the indefinite LQ control problem by considering forward and backward stochastic difference equations (FBSDEs). Specifically, through an orthogonal decomposition method, we introduce a novel technique to decouple the FBSDEs, facilitating the derivation of optimal controllers via non-symmetric Riccati equations. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107569"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348263","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107526
Li Li, Xingyu Tian
In this paper, a multi-sensor fusion estimation problem is investigated for a nonlinear cyber–physical system, where insecure sensor measurements may be falsified by false data injection (FDI) attacks. To make the system capable of proactively defending against the attacks, a multi-channel transmission strategy with stochastic communication protocol (SCP) is established for each insecure sensor. Due to the sensitivity of Kullback–Leibler divergence (KLD) to outliers generated by FDI attacks, a KLD-based detector is designed without relying on past data. A novel method is proposed by modifying the cross covariance according to detection results and a modified matrix-weighted fusion (MMWF) algorithm is presented. The fusion estimation error is derived to be bounded under certain conditions. Finally, a uniformly accelerated linear motion example confirms the validity of the theoretical derivations.
{"title":"Modified matrix-weighted fusion estimation for cyber–physical systems under FDI attacks","authors":"Li Li, Xingyu Tian","doi":"10.1016/j.jfranklin.2025.107526","DOIUrl":"10.1016/j.jfranklin.2025.107526","url":null,"abstract":"<div><div>In this paper, a multi-sensor fusion estimation problem is investigated for a nonlinear cyber–physical system, where insecure sensor measurements may be falsified by false data injection (FDI) attacks. To make the system capable of proactively defending against the attacks, a multi-channel transmission strategy with stochastic communication protocol (SCP) is established for each insecure sensor. Due to the sensitivity of Kullback–Leibler divergence (KLD) to outliers generated by FDI attacks, a KLD-based detector is designed without relying on past data. A novel method is proposed by modifying the cross covariance according to detection results and a modified matrix-weighted fusion (MMWF) algorithm is presented. The fusion estimation error is derived to be bounded under certain conditions. Finally, a uniformly accelerated linear motion example confirms the validity of the theoretical derivations.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107526"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143342734","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2025.107570
Ruihua Wang , Xinru Fan , Ticao Jiao , Dong Yang , Shuai Wang , Gan Liu
A resilient event-triggered scheme is proposed to investigate the input-to-state stability (ISS) of networked switched systems subject to denial-of-service (DoS) attacks under fast/slow mode-dependent average dwell time (MDADT). The use of the resilient event-triggered scheme conserves network resources, ensuring that the maximum asynchronous time is smaller than one sampling period, and swiftly detecting the cessation of DoS attacks. For the purpose of analyzing the ISS of the networked switched system, a novel piecewise Lyapunov function is proposed that accounts for the combined impacts of DoS attacks and the resilient event-triggered scheme. The fast MDADT switching is employed to deal with the unstable modes of the closed-loop system. Then sufficient conditions are established to guarantee the ISS of networked switched system facing DoS attacks, which reveal the combined effect of DoS attacks, sampling period and event-triggered constraint on the system stability. Eventually, the efficacy of the aforementioned approach is validated in the simulation through a comparative study.
{"title":"Resilient event-triggered control of networked switched systems under DoS attacks","authors":"Ruihua Wang , Xinru Fan , Ticao Jiao , Dong Yang , Shuai Wang , Gan Liu","doi":"10.1016/j.jfranklin.2025.107570","DOIUrl":"10.1016/j.jfranklin.2025.107570","url":null,"abstract":"<div><div>A resilient event-triggered scheme is proposed to investigate the input-to-state stability (ISS) of networked switched systems subject to denial-of-service (DoS) attacks under fast/slow mode-dependent average dwell time (MDADT). The use of the resilient event-triggered scheme conserves network resources, ensuring that the maximum asynchronous time is smaller than one sampling period, and swiftly detecting the cessation of DoS attacks. For the purpose of analyzing the ISS of the networked switched system, a novel piecewise Lyapunov function is proposed that accounts for the combined impacts of DoS attacks and the resilient event-triggered scheme. The fast MDADT switching is employed to deal with the unstable modes of the closed-loop system. Then sufficient conditions are established to guarantee the ISS of networked switched system facing DoS attacks, which reveal the combined effect of DoS attacks, sampling period and event-triggered constraint on the system stability. Eventually, the efficacy of the aforementioned approach is validated in the simulation through a comparative study.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107570"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143369729","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 : 2025-02-01DOI: 10.1016/j.jfranklin.2024.107493
Linge Miao , Xiangliang Sun , Xiaona Song , Shuai Song
This study develops a consensus control technique for a class of multiagent systems (MASs) modeled using partial differential equations (PDEs) of the parabolic type, which implies that the state of each agent is space–time dependent. Furthermore, when the spatial factor is considered in the modeling of the system, the modeled system generates huge amounts of data, which can pose a problem in view of the limited network bandwidth. This problem is overcome by employing a spatial point measurement approach, which is used in this study for the first time, to reduce the amount of data transmission. Furthermore, the update frequency of controllers and actuators is reduced by using dual event-triggered mechanisms (ETMs). In view of the mismatch between measurement and control points, non-collocated pointwise control is used to achieve consensus. Finally, a numerical simulation is performed to verify the theory proposed in this paper, moreover, the comparative experiments illustrate the superiority of the spatial point measurement approach and dual event-triggered mechanisms.
{"title":"Consensus for PDE-based multiagent systems under dual event-triggered mechanisms","authors":"Linge Miao , Xiangliang Sun , Xiaona Song , Shuai Song","doi":"10.1016/j.jfranklin.2024.107493","DOIUrl":"10.1016/j.jfranklin.2024.107493","url":null,"abstract":"<div><div>This study develops a consensus control technique for a class of multiagent systems (MASs) modeled using partial differential equations (PDEs) of the parabolic type, which implies that the state of each agent is space–time dependent. Furthermore, when the spatial factor is considered in the modeling of the system, the modeled system generates huge amounts of data, which can pose a problem in view of the limited network bandwidth. This problem is overcome by employing a spatial point measurement approach, which is used in this study for the first time, to reduce the amount of data transmission. Furthermore, the update frequency of controllers and actuators is reduced by using dual event-triggered mechanisms (ETMs). In view of the mismatch between measurement and control points, non-collocated pointwise control is used to achieve consensus. Finally, a numerical simulation is performed to verify the theory proposed in this paper, moreover, the comparative experiments illustrate the superiority of the spatial point measurement approach and dual event-triggered mechanisms.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 4","pages":"Article 107493"},"PeriodicalIF":3.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145406","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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