Pub Date : 2025-09-19DOI: 10.1109/TSMC.2025.3604209
{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/TSMC.2025.3604209","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3604209","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"C3-C3"},"PeriodicalIF":8.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11173423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089944","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}
Pub Date : 2025-09-18DOI: 10.1109/TSMC.2025.3606857
Yifan Li;Xifeng Gao;Xingchen Li;Kai Zhang;Okyay Kaynak;Jiubin Tan
Autonomous underwater vehicles (AUVs) face significant challenges in trajectory tracking due to nonlinear dynamics, actuator faults, and environmental disturbances. To address these issues, this article proposes a novel fault-tolerant control strategy that ensures fixed-time trajectory tracking with prescribed accuracy for underactuated AUVs. The proposed approach integrates boundary functions with a constraint-handling mechanism, enabling guaranteed tracking performance within a fixed time horizon while satisfying output constraints. Unlike existing approaches, the controller does not rely on accurate system models, parameter estimation, or external observers, and avoids the computation of virtual control derivatives, resulting in reduced computational complexity. Moreover, the control scheme maintains robustness against time-varying actuator faults and environmental disturbances without auxiliary adaptation or learning mechanisms. Simulation results demonstrate the effectiveness and superior performance of the proposed approach compared with existing methods, validating its capability to maintain tracking accuracy and closed-loop stability under adverse operating conditions.
{"title":"Fault-Tolerant Control for Autonomous Underwater Vehicles With Prescribed Tracking Accuracy","authors":"Yifan Li;Xifeng Gao;Xingchen Li;Kai Zhang;Okyay Kaynak;Jiubin Tan","doi":"10.1109/TSMC.2025.3606857","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3606857","url":null,"abstract":"Autonomous underwater vehicles (AUVs) face significant challenges in trajectory tracking due to nonlinear dynamics, actuator faults, and environmental disturbances. To address these issues, this article proposes a novel fault-tolerant control strategy that ensures fixed-time trajectory tracking with prescribed accuracy for underactuated AUVs. The proposed approach integrates boundary functions with a constraint-handling mechanism, enabling guaranteed tracking performance within a fixed time horizon while satisfying output constraints. Unlike existing approaches, the controller does not rely on accurate system models, parameter estimation, or external observers, and avoids the computation of virtual control derivatives, resulting in reduced computational complexity. Moreover, the control scheme maintains robustness against time-varying actuator faults and environmental disturbances without auxiliary adaptation or learning mechanisms. Simulation results demonstrate the effectiveness and superior performance of the proposed approach compared with existing methods, validating its capability to maintain tracking accuracy and closed-loop stability under adverse operating conditions.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8531-8543"},"PeriodicalIF":8.7,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335300","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}
Pub Date : 2025-09-18DOI: 10.1109/TSMC.2025.3605649
Xujie Wan;Wenjie Li;Guangwei Gao;Huimin Lu;Jian Yang;Chia-Wen Lin
Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Because of numerous features at different scales in hybrid networks, how to fuse these multiscale features and promote their complementarity is crucial for enhancing FSR. However, existing hybrid network-based FSR methods ignore this, only simply combining the Transformer and CNN. To address this issue, we propose an attention-guided multiscale interaction network (AMINet), which incorporates local and global feature interactions, as well as encoder–decoder phase feature interactions. Specifically, we propose a local and global feature interaction (LGFI) module to promote the fusion of global features and the local features extracted from different receptive fields by our residual depth feature extraction (RDFE) module. Additionally, we propose a selective kernel attention fusion (SKAF) module to adaptively select fusions of different features within the LGFI and encoder–decoder phases. Our above design allows the free flow of multiscale features from within modules and between the encoder and decoder, which can promote the complementarity of different scale features to enhance FSR. Comprehensive experiments confirm that our method consistently performs well with less computational consumption and faster inference.
{"title":"Attention-Guided Multiscale Interaction Network for Face Super-Resolution","authors":"Xujie Wan;Wenjie Li;Guangwei Gao;Huimin Lu;Jian Yang;Chia-Wen Lin","doi":"10.1109/TSMC.2025.3605649","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3605649","url":null,"abstract":"Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Because of numerous features at different scales in hybrid networks, how to fuse these multiscale features and promote their complementarity is crucial for enhancing FSR. However, existing hybrid network-based FSR methods ignore this, only simply combining the Transformer and CNN. To address this issue, we propose an attention-guided multiscale interaction network (AMINet), which incorporates local and global feature interactions, as well as encoder–decoder phase feature interactions. Specifically, we propose a local and global feature interaction (LGFI) module to promote the fusion of global features and the local features extracted from different receptive fields by our residual depth feature extraction (RDFE) module. Additionally, we propose a selective kernel attention fusion (SKAF) module to adaptively select fusions of different features within the LGFI and encoder–decoder phases. Our above design allows the free flow of multiscale features from within modules and between the encoder and decoder, which can promote the complementarity of different scale features to enhance FSR. Comprehensive experiments confirm that our method consistently performs well with less computational consumption and faster inference.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8638-8650"},"PeriodicalIF":8.7,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335295","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}
Pub Date : 2025-09-16DOI: 10.1109/TSMC.2025.3606937
Yinghong Zhao;Likui Wang;Hak-Keung Lam
This article investigates the problem of event-based strictly dissipative filtering for stochastic fuzzy complex networks (SFCNs) subject to multiple cyberattacks, including deception attacks and denial-of-service (DoS) attacks. A resilient event-triggered mechanism (ETM) is proposed to reduce the communication burden while effectively countering these cyberattacks. The membership functions are assumed to be mismatched due to the impact of the network environment and sampling behavior. Furthermore, the system dynamics are modeled using Itô-type stochastic differential equations, which include deterministic fuzzy complex networks (CNs) as a special case. Unlike previous studies on stochastic systems, the auxiliary vector function method is employed to introduce more time-varying delay information into the piecewise Lyapunov–Krasovskii functional (LKF), thus reducing conservatism. Consequently, a series of delay-dependent sufficient conditions is derived to ensure the exponentially mean-square stability (EMSS) and strict dissipativity of the filtering error system. Finally, the effectiveness of the proposed method is demonstrated through an illustrative example.
{"title":"Event-Triggered Dissipative Filtering for Stochastic Fuzzy Complex Networks Under Multiple Cyberattacks","authors":"Yinghong Zhao;Likui Wang;Hak-Keung Lam","doi":"10.1109/TSMC.2025.3606937","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3606937","url":null,"abstract":"This article investigates the problem of event-based strictly dissipative filtering for stochastic fuzzy complex networks (SFCNs) subject to multiple cyberattacks, including deception attacks and denial-of-service (DoS) attacks. A resilient event-triggered mechanism (ETM) is proposed to reduce the communication burden while effectively countering these cyberattacks. The membership functions are assumed to be mismatched due to the impact of the network environment and sampling behavior. Furthermore, the system dynamics are modeled using Itô-type stochastic differential equations, which include deterministic fuzzy complex networks (CNs) as a special case. Unlike previous studies on stochastic systems, the auxiliary vector function method is employed to introduce more time-varying delay information into the piecewise Lyapunov–Krasovskii functional (LKF), thus reducing conservatism. Consequently, a series of delay-dependent sufficient conditions is derived to ensure the exponentially mean-square stability (EMSS) and strict dissipativity of the filtering error system. Finally, the effectiveness of the proposed method is demonstrated through an illustrative example.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8612-8624"},"PeriodicalIF":8.7,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335301","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}
Pub Date : 2025-09-16DOI: 10.1109/TSMC.2025.3607885
Fujin Jia;Quanxin Zhu
This article investigates nonovershooting tracking control for a class of multiple-input–multiple-output (MIMO) nonlinear systems. Nonovershooting tracking control is desired in various practical situations, yet remains a challenging task with limited existing research. While the MIMO nonlinear system better represents real-world scenarios, the specific algorithm for nonovershooting tracking control has not been previously reported. In this study, a controller is designed to ensure system stability initially, while also achieving a closed-loop system for easy tracking error analysis. By deriving the expression of tracking error, a broad range of nonovershooting tracking conditions is identified through analytical analysis. The proposed nonovershooting control is shown to offer more extensive nonovershooting conditions compared to existing approaches, thereby reducing conservatism. Furthermore, this algorithm eliminates overshoot in MIMO nonlinear systems. Its effectiveness is validated through application to a two-degree-of-freedom robot manipulator.
{"title":"Conditions for Guaranteeing Nonovershooting Control of MIMO Nonlinear Systems With Application to Robot Manipulator","authors":"Fujin Jia;Quanxin Zhu","doi":"10.1109/TSMC.2025.3607885","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3607885","url":null,"abstract":"This article investigates nonovershooting tracking control for a class of multiple-input–multiple-output (MIMO) nonlinear systems. Nonovershooting tracking control is desired in various practical situations, yet remains a challenging task with limited existing research. While the MIMO nonlinear system better represents real-world scenarios, the specific algorithm for nonovershooting tracking control has not been previously reported. In this study, a controller is designed to ensure system stability initially, while also achieving a closed-loop system for easy tracking error analysis. By deriving the expression of tracking error, a broad range of nonovershooting tracking conditions is identified through analytical analysis. The proposed nonovershooting control is shown to offer more extensive nonovershooting conditions compared to existing approaches, thereby reducing conservatism. Furthermore, this algorithm eliminates overshoot in MIMO nonlinear systems. Its effectiveness is validated through application to a two-degree-of-freedom robot manipulator.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8651-8660"},"PeriodicalIF":8.7,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335333","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}
Pub Date : 2025-09-15DOI: 10.1109/TSMC.2025.3604832
Haojie Liu;Jianyang Gu;Zhiyong Li;Mingyu Wang;Q. M. Jonathan Wu;Wei Jiang
Visible–infrared person re-identification (VI-ReID) focuses on accurately matching individuals across different imaging modalities. Existing studies focus on generating modality-consistent images at the pixel level through the use of generative adversarial networks (GANs) to mitigate the impact of modality discrepancies. However, these methods face significant challenges in overcoming the limitation that synthesized samples from different modalities may suffer from semantic distortion. In this work, we propose an online one-stage style fuzzy normalization (SFN) method to generate modality-fuzzy features in the latent space while regularizing the model’s predictions. Specifically, SFN adaptively mixes the feature statistics of two random modality instances of the same identity in a single forward pass during training. In this process, to enhance the richness of modality interaction information, we design a novel causality balance loss, which enforces the generated fuzzy features to be independent of their initial modality while simultaneously encouraging them to align more closely with the other modality. Furthermore, we introduce an identity-aware consistency loss to regularize the predictions between the original and SFN-generated features to ensure semantic consistency. In contrast to prior work, SFN is a plug-and-play module that does not rely on any generative-based models, making it highly adaptable to various network architectures. Extensive experiments were performed on three public cross-modality datasets to ensure fair and reliable comparisons. The empirical results demonstrate the clear superiority of our method over previous state-of-the-art methods.
{"title":"CoMix: Collaborative Mixed Learning via Style Fuzzy Normalization for Visible–Infrared Person Re-Identification","authors":"Haojie Liu;Jianyang Gu;Zhiyong Li;Mingyu Wang;Q. M. Jonathan Wu;Wei Jiang","doi":"10.1109/TSMC.2025.3604832","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3604832","url":null,"abstract":"Visible–infrared person re-identification (VI-ReID) focuses on accurately matching individuals across different imaging modalities. Existing studies focus on generating modality-consistent images at the pixel level through the use of generative adversarial networks (GANs) to mitigate the impact of modality discrepancies. However, these methods face significant challenges in overcoming the limitation that synthesized samples from different modalities may suffer from semantic distortion. In this work, we propose an online one-stage style fuzzy normalization (SFN) method to generate modality-fuzzy features in the latent space while regularizing the model’s predictions. Specifically, SFN adaptively mixes the feature statistics of two random modality instances of the same identity in a single forward pass during training. In this process, to enhance the richness of modality interaction information, we design a novel causality balance loss, which enforces the generated fuzzy features to be independent of their initial modality while simultaneously encouraging them to align more closely with the other modality. Furthermore, we introduce an identity-aware consistency loss to regularize the predictions between the original and SFN-generated features to ensure semantic consistency. In contrast to prior work, SFN is a plug-and-play module that does not rely on any generative-based models, making it highly adaptable to various network architectures. Extensive experiments were performed on three public cross-modality datasets to ensure fair and reliable comparisons. The empirical results demonstrate the clear superiority of our method over previous state-of-the-art methods.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8572-8586"},"PeriodicalIF":8.7,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335290","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}
Pub Date : 2025-09-12DOI: 10.1109/TSMC.2025.3605860
Shiyu Zhang;Guangren Duan
A robust adaptive control problem of fully actuated systems (FASs) with perturbed input matrices, unknown time-varying parameters, and partial knowledge of uncertainty bounds is considered. Unlike the existing results on FASs with perturbed input matrices, the restriction that the bound of the nonlinear uncertainty must be known is removed and a certain unknown constant is now allowed to be included in the bound. A novel robust adaptive controller is developed, where the adaptive term adapts to the effects of the time-varying unknown parameters in the FAS and the unknown constant in the uncertainty bound, and the robust term overcomes the influence of the remaining uncertain part caused by the perturbed input matrix. The designed controller enables the states of the closed-loop system and the estimation errors to be globally bounded. Finally, the developed method is successfully applied to the control of both a numerical example and an electromechanical system, and the effectiveness is proven by the comparative simulation results with the existing methods.
{"title":"Control of Fully Actuated Systems With Perturbed Input Matrices and Partial Knowledge of Uncertainty Bounds","authors":"Shiyu Zhang;Guangren Duan","doi":"10.1109/TSMC.2025.3605860","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3605860","url":null,"abstract":"A robust adaptive control problem of fully actuated systems (FASs) with perturbed input matrices, unknown time-varying parameters, and partial knowledge of uncertainty bounds is considered. Unlike the existing results on FASs with perturbed input matrices, the restriction that the bound of the nonlinear uncertainty must be known is removed and a certain unknown constant is now allowed to be included in the bound. A novel robust adaptive controller is developed, where the adaptive term adapts to the effects of the time-varying unknown parameters in the FAS and the unknown constant in the uncertainty bound, and the robust term overcomes the influence of the remaining uncertain part caused by the perturbed input matrix. The designed controller enables the states of the closed-loop system and the estimation errors to be globally bounded. Finally, the developed method is successfully applied to the control of both a numerical example and an electromechanical system, and the effectiveness is proven by the comparative simulation results with the existing methods.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8599-8611"},"PeriodicalIF":8.7,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335258","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}
Pub Date : 2025-09-12DOI: 10.1109/TSMC.2025.3605976
Jie Zhang;Ying Zhang;Wen-Nian Qi
The stabilization problem for discrete-time linear systems subject to both state and input delays is addressed when the state variables are not available. Full-order and reduced-order observers with output feedback are designed for state estimation. Then, observer-based predictors with an explicit form are developed to predict future states using fundamental matrices. Next, two classes of state observer-based predictor feedback controllers are proposed to solve the stabilization problem. It is shown that the characteristic polynomial of the closed-loop system under the proposed control law is the product of the characteristic polynomials of the input-delay-free closed-loop system and the state estimation error system. Finally, two examples are employed to validate the effectiveness of the proposed controllers.
{"title":"State Observer-Based Predictor Feedback Control for Discrete-Time Linear Systems With State and Input Delays via Fundamental Matrices","authors":"Jie Zhang;Ying Zhang;Wen-Nian Qi","doi":"10.1109/TSMC.2025.3605976","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3605976","url":null,"abstract":"The stabilization problem for discrete-time linear systems subject to both state and input delays is addressed when the state variables are not available. Full-order and reduced-order observers with output feedback are designed for state estimation. Then, observer-based predictors with an explicit form are developed to predict future states using fundamental matrices. Next, two classes of state observer-based predictor feedback controllers are proposed to solve the stabilization problem. It is shown that the characteristic polynomial of the closed-loop system under the proposed control law is the product of the characteristic polynomials of the input-delay-free closed-loop system and the state estimation error system. Finally, two examples are employed to validate the effectiveness of the proposed controllers.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8492-8505"},"PeriodicalIF":8.7,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335281","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}
This article addresses the disturbance decoupling problem (DDP) of probabilistic Boolean networks (PBNs). Existing research on the DDP of Boolean networks (BNs) has predominantly concentrated on deterministic BNs (DBNs), which inadequately model the complexities of real-world systems, particularly those exhibiting stochastic behavior and uncertainty. We introduce two definitions tailored to PBNs: disturbance decoupling in distribution and disturbance decoupling with probability one. Utilizing an algebraic representation framework, we derive algebraic conditions for both types of disturbance decoupling. Additionally, we employ a vertex partitioning approach to establish graphical conditions pertinent to these disturbance decoupling types. Our investigation further reveals the connections between DBNs and PBNs concerning disturbance decoupling. To demonstrate the effectiveness of our theoretical results, we present three examples.
{"title":"Disturbance Decoupling of Probabilistic Boolean Networks","authors":"Yifeng Li;Ying Cheng;Haitao Li;Zhichun Yang;Tingwen Huang","doi":"10.1109/TSMC.2025.3605616","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3605616","url":null,"abstract":"This article addresses the disturbance decoupling problem (DDP) of probabilistic Boolean networks (PBNs). Existing research on the DDP of Boolean networks (BNs) has predominantly concentrated on deterministic BNs (DBNs), which inadequately model the complexities of real-world systems, particularly those exhibiting stochastic behavior and uncertainty. We introduce two definitions tailored to PBNs: disturbance decoupling in distribution and disturbance decoupling with probability one. Utilizing an algebraic representation framework, we derive algebraic conditions for both types of disturbance decoupling. Additionally, we employ a vertex partitioning approach to establish graphical conditions pertinent to these disturbance decoupling types. Our investigation further reveals the connections between DBNs and PBNs concerning disturbance decoupling. To demonstrate the effectiveness of our theoretical results, we present three examples.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8587-8598"},"PeriodicalIF":8.7,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335294","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}
Pub Date : 2025-09-10DOI: 10.1109/TSMC.2025.3605859
Cui-Hua Zhang;Ze-Yun Hu;Yu-Jia Li;Ying Zhang;Chang-Chun Hua;Yue-Ying Liu
This article explores the issue of event-triggered prescribed-time tracking control for uncertain nonlinear systems with unknown parameters and external disturbances. A novel adaptive event-triggered proportional–integral (PI) funnel control protocol is proposed, where the switching threshold event-triggered strategy is adopted to conserve communication resources while guaranteeing the expected control performance. To obtain the global results, a new method combining adaptive techniques with the design of prescribed functions with infinite initial values is presented. Compared with the existing schemes, a more concise PI-funnel control method is provided to realize the global prescribed-time tracking control performance, which avoids the external disturbance estimation and calculation of derivatives at each step of the traditional backstepping method. Finally, the effectiveness of the proposed method is illustrated through two simulation demonstrations.
{"title":"Event-Based Adaptive PI-Funnel Global Tracking Control for Uncertain Nonlinear Systems","authors":"Cui-Hua Zhang;Ze-Yun Hu;Yu-Jia Li;Ying Zhang;Chang-Chun Hua;Yue-Ying Liu","doi":"10.1109/TSMC.2025.3605859","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3605859","url":null,"abstract":"This article explores the issue of event-triggered prescribed-time tracking control for uncertain nonlinear systems with unknown parameters and external disturbances. A novel adaptive event-triggered proportional–integral (PI) funnel control protocol is proposed, where the switching threshold event-triggered strategy is adopted to conserve communication resources while guaranteeing the expected control performance. To obtain the global results, a new method combining adaptive techniques with the design of prescribed functions with infinite initial values is presented. Compared with the existing schemes, a more concise PI-funnel control method is provided to realize the global prescribed-time tracking control performance, which avoids the external disturbance estimation and calculation of derivatives at each step of the traditional backstepping method. Finally, the effectiveness of the proposed method is illustrated through two simulation demonstrations.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 11","pages":"8481-8491"},"PeriodicalIF":8.7,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335282","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}
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