Pub Date : 2026-01-26DOI: 10.1109/TCYB.2025.3646492
Yi Yu, Guo-Ping Liu, Zhong-Hua Pang, Jian Sun, Rongni Yang
With the increasingly integrated nature of networked control systems (NCSs), security has become a challenging issue for their widespread deployment. Although resilient control methods against various attacks have been reported, the analysis and design of defense mechanisms for NCSs still require fresh efforts. To this end, this article is concerned with the security control of a class of NCSs vulnerable to smart false data injection (FDI) attacks. Specifically, the scenario of output tracking of NCSs is considered, where the communication between sensors and controllers, as well as between controllers and actuators, is compromised by sophisticated malicious adversaries. To enhance security, peer-to-peer (P2P) networks with blockchain technologies are utilized instead of traditional communication patterns to transmit measurement and control signals. Unlike previous work, this work carefully designs an optimal blockchain consensus policy by perceiving the performance of NCSs and develops a resilient dynamic output tracking controller based on this policy. The formulation of the consensus policy is derived from a game-theoretic framework that models the interaction between the blockchain and the malicious adversary, enabling deep integration of blockchain technology with NCSs. With the proposed approach, the adverse effects of malicious FDI attacks can be greatly mitigated by balancing energy consumption and tracking performance. Finally, the applicability of the proposed security control strategy is verified in a real-world power system.
{"title":"Blockchain-Assisted Intelligent Resilient Tracking Control of Networked Systems.","authors":"Yi Yu, Guo-Ping Liu, Zhong-Hua Pang, Jian Sun, Rongni Yang","doi":"10.1109/TCYB.2025.3646492","DOIUrl":"https://doi.org/10.1109/TCYB.2025.3646492","url":null,"abstract":"<p><p>With the increasingly integrated nature of networked control systems (NCSs), security has become a challenging issue for their widespread deployment. Although resilient control methods against various attacks have been reported, the analysis and design of defense mechanisms for NCSs still require fresh efforts. To this end, this article is concerned with the security control of a class of NCSs vulnerable to smart false data injection (FDI) attacks. Specifically, the scenario of output tracking of NCSs is considered, where the communication between sensors and controllers, as well as between controllers and actuators, is compromised by sophisticated malicious adversaries. To enhance security, peer-to-peer (P2P) networks with blockchain technologies are utilized instead of traditional communication patterns to transmit measurement and control signals. Unlike previous work, this work carefully designs an optimal blockchain consensus policy by perceiving the performance of NCSs and develops a resilient dynamic output tracking controller based on this policy. The formulation of the consensus policy is derived from a game-theoretic framework that models the interaction between the blockchain and the malicious adversary, enabling deep integration of blockchain technology with NCSs. With the proposed approach, the adverse effects of malicious FDI attacks can be greatly mitigated by balancing energy consumption and tracking performance. Finally, the applicability of the proposed security control strategy is verified in a real-world power system.</p>","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":10.5,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146051779","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 : 2026-01-23DOI: 10.1109/tcyb.2026.3651519
Han Wu,Qinglei Hu,Jianying Zheng,Xiaodong Shao,Yueyang Liu,Dongyu Li
This article proposes a novel discounted inverse reinforcement learning (DIRL) algorithm for linear quadratic (LQ) control of unknown continuous-time (CT) systems with partially observable states and an unknown discounted value function. Existing DIRL methods predominantly rely on full-state feedback, limiting their applicability to practical scenarios where only input-output data are available. To this end, a state reconstruction method is designed for the system controlled by an expert using the measured desired output. Based on this, a model-free output-feedback (OPFB) DIRL algorithm is presented to iteratively solve the unknown value function and the corresponding optimal OPFB control policy equivalent to the expert control policy. The convergence of the proposed algorithm and the nonuniqueness of solutions are rigorously analyzed. Finally, comprehensive simulations reveal the effectiveness of the proposed algorithm in recovering the expert control policy and its superior computational efficiency compared to state-of-the-art (SOTA) methods.
{"title":"Output-Feedback Control of Linear Continuous-Time Systems Using Discounted Inverse Reinforcement Learning.","authors":"Han Wu,Qinglei Hu,Jianying Zheng,Xiaodong Shao,Yueyang Liu,Dongyu Li","doi":"10.1109/tcyb.2026.3651519","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3651519","url":null,"abstract":"This article proposes a novel discounted inverse reinforcement learning (DIRL) algorithm for linear quadratic (LQ) control of unknown continuous-time (CT) systems with partially observable states and an unknown discounted value function. Existing DIRL methods predominantly rely on full-state feedback, limiting their applicability to practical scenarios where only input-output data are available. To this end, a state reconstruction method is designed for the system controlled by an expert using the measured desired output. Based on this, a model-free output-feedback (OPFB) DIRL algorithm is presented to iteratively solve the unknown value function and the corresponding optimal OPFB control policy equivalent to the expert control policy. The convergence of the proposed algorithm and the nonuniqueness of solutions are rigorously analyzed. Finally, comprehensive simulations reveal the effectiveness of the proposed algorithm in recovering the expert control policy and its superior computational efficiency compared to state-of-the-art (SOTA) methods.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"42 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034075","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 : 2026-01-23DOI: 10.1109/tcyb.2026.3650907
Zhi-Hui Fu,Ming-Feng Ge,Teng-Fei Ding,Zhi-Wei Liu
In this article, we investigate the task optimization for fixed-time control of intermittent human-robot interaction, where a human operator assists the robot intermittently in selecting the most appropriate Pareto solution. First, as for the Lyapunov fixed-time stability criterion inequality with and without the constant term, we all derive the Lyapunov stability conditions with time-varying exponents and coefficients, providing us with more flexibility and freedom to shape the contour of the convergence near the Lyapunov stable equilibrium. We then use them to propose a hierarchical fixed-time event-triggered optimization (HFTEO) algorithm based on human-oriented scheme, where the so-called human-oriented scheme means that the components constituting task information are known only to the human operator, but not to the robot, which is beneficial to ensure the confidentiality and security of the task. Simulation results are given to show the effectiveness of the proposed Lyapunov stability conditions and algorithm.
{"title":"Task Optimization for Fixed-Time Control of Intermittent Human-Robot Interaction With Time-Varying Exponents and Coefficients.","authors":"Zhi-Hui Fu,Ming-Feng Ge,Teng-Fei Ding,Zhi-Wei Liu","doi":"10.1109/tcyb.2026.3650907","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3650907","url":null,"abstract":"In this article, we investigate the task optimization for fixed-time control of intermittent human-robot interaction, where a human operator assists the robot intermittently in selecting the most appropriate Pareto solution. First, as for the Lyapunov fixed-time stability criterion inequality with and without the constant term, we all derive the Lyapunov stability conditions with time-varying exponents and coefficients, providing us with more flexibility and freedom to shape the contour of the convergence near the Lyapunov stable equilibrium. We then use them to propose a hierarchical fixed-time event-triggered optimization (HFTEO) algorithm based on human-oriented scheme, where the so-called human-oriented scheme means that the components constituting task information are known only to the human operator, but not to the robot, which is beneficial to ensure the confidentiality and security of the task. Simulation results are given to show the effectiveness of the proposed Lyapunov stability conditions and algorithm.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"7 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034077","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 investigates the smooth control problem of switched fuzzy systems, where the modes asynchronously switch under a partly stochastic sojourn time (PSST) switching signal, i.e., a duration of the sojourn time is governed by a random distribution. The formulated PSST switching signal is composed of a mode-dependent activated time and a duration subject to certain stochastic processes, which covers the conventional (average) dwell time (DT) switching signals or stochastic switching signals as special cases. Considering the measuring and computing delay in mode and membership degree identifying of the fuzzy switched systems, the asynchronous phenomena caused by unmatched case between control and system modes are included in the PSST switching signal, and a detected-mode-based Lyapunov candidate is formulated for the mean-square stability (MSS) and robustness analysis, which has not been considered before. To overcome the undesired control bump between adjacent modes, a multistage membership degree interpolation approach is proposed to obtain a smooth control transition after the asynchronous duration to carry out an anti-asynchronously stochastically smoothly switched fuzzy controller (A2S3-FC), unlike the existing literature that only considers part of the property of the practical systems. The effectiveness and the advantages of the proposed A2S3-FC are verified via a numerical example and a simulation of aerial manipulator attitude control.
{"title":"Smooth Control of Asynchronously Switched Fuzzy Systems With Partly Stochastic Sojourn Time.","authors":"Yihang Ding,Ye Liang,Jianan Yang,Yifei Dong,Lixian Zhang","doi":"10.1109/tcyb.2026.3651915","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3651915","url":null,"abstract":"This article investigates the smooth control problem of switched fuzzy systems, where the modes asynchronously switch under a partly stochastic sojourn time (PSST) switching signal, i.e., a duration of the sojourn time is governed by a random distribution. The formulated PSST switching signal is composed of a mode-dependent activated time and a duration subject to certain stochastic processes, which covers the conventional (average) dwell time (DT) switching signals or stochastic switching signals as special cases. Considering the measuring and computing delay in mode and membership degree identifying of the fuzzy switched systems, the asynchronous phenomena caused by unmatched case between control and system modes are included in the PSST switching signal, and a detected-mode-based Lyapunov candidate is formulated for the mean-square stability (MSS) and robustness analysis, which has not been considered before. To overcome the undesired control bump between adjacent modes, a multistage membership degree interpolation approach is proposed to obtain a smooth control transition after the asynchronous duration to carry out an anti-asynchronously stochastically smoothly switched fuzzy controller (A2S3-FC), unlike the existing literature that only considers part of the property of the practical systems. The effectiveness and the advantages of the proposed A2S3-FC are verified via a numerical example and a simulation of aerial manipulator attitude control.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"95 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015180","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 : 2026-01-21DOI: 10.1109/tcyb.2026.3652427
Lei Chu,Yungang Liu
This article proposes a new adaptive event-triggered controller with prescribed tracking performance for a class of uncertain nonlinear systems. The controller is global, instead of semiglobal, by eliminating the initial-condition-dependence on the performance function. In contrast to the existing results, the controller design is tight to reduce conservatism, in which two enablers are involved. First, the controller fully leverages available information on system nonlinearities, rather than discarding the information as is done in the context of funnel control (FC). This enables the controller to more efficiently counteract the nonlinearities, potentially avoiding unnecessarily large control effort, thereby reducing conservatism. Second, dedicated dynamic compensations are introduced with the help of tuning functions to compensate for the intrinsic uncertainties appearing in the execution error, system nonlinearities, and control coefficients. In this way, estimating conservative bounds of multiple uncertain parameters is circumvented, and especially, inequality estimates, including completing squares, are largely avoided, thereby also reducing conservatism. To further improve communication efficiency, the proposed control scheme is extended to the scenario where the information transmission from sensor to controller is also event-triggered, by delicately designing a double-sided event-triggering mechanism. A classical pendulum system is utilized to verify the effectiveness and superiority of the proposed method.
{"title":"A Tight Adaptive Event-Triggered Controller With Global Prescribed Tracking Performance.","authors":"Lei Chu,Yungang Liu","doi":"10.1109/tcyb.2026.3652427","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3652427","url":null,"abstract":"This article proposes a new adaptive event-triggered controller with prescribed tracking performance for a class of uncertain nonlinear systems. The controller is global, instead of semiglobal, by eliminating the initial-condition-dependence on the performance function. In contrast to the existing results, the controller design is tight to reduce conservatism, in which two enablers are involved. First, the controller fully leverages available information on system nonlinearities, rather than discarding the information as is done in the context of funnel control (FC). This enables the controller to more efficiently counteract the nonlinearities, potentially avoiding unnecessarily large control effort, thereby reducing conservatism. Second, dedicated dynamic compensations are introduced with the help of tuning functions to compensate for the intrinsic uncertainties appearing in the execution error, system nonlinearities, and control coefficients. In this way, estimating conservative bounds of multiple uncertain parameters is circumvented, and especially, inequality estimates, including completing squares, are largely avoided, thereby also reducing conservatism. To further improve communication efficiency, the proposed control scheme is extended to the scenario where the information transmission from sensor to controller is also event-triggered, by delicately designing a double-sided event-triggering mechanism. A classical pendulum system is utilized to verify the effectiveness and superiority of the proposed method.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"382 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015432","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 proposes a resilient control framework for securing cyber-physical systems (CPSs), specifically addressing nonlinear descriptor systems operating under communication constraints and subject to sensor and actuator attacks. We integrate Takagi-Sugeno (T-S) fuzzy models with a Q-learning-based event-triggered mechanism (ETM) and adopt a sliding-mode control strategy to establish a resilient security architecture that adaptively balances operational efficiency with robust protection against cyber-physical threats. A major contribution of this work lies in designing an adaptive fuzzy sliding-mode observer (SMO) with mismatched premise variables for the estimation of compromised system states. Additionally, a sliding-mode controller (SMC) is synthesized to maintain closed-loop admissibility and ensure the reachability of sliding surfaces. We advance beyond the existing approaches by employing the secretary bird optimization algorithm (SBOA) to optimize controller and observer gains, thereby solving the nonconvex optimization challenges present in controller and observer design. The effectiveness of the proposed method is validated through extensive Monte Carlo simulations on a truck-trailer system. These simulations demonstrate the efficacy of the approach in maintaining system stability and performance under various attack scenarios, thereby making a significant contribution to the security of nonlinear systems in networked environments.
{"title":"Analysis and Optimization of Secure Sliding Mode Observer-Based Control in Nonlinear Descriptor Systems Under Attacks.","authors":"Mourad Kchaou,M Syed Ali,Rabeh Abbassi,Houssem Jerbi","doi":"10.1109/tcyb.2026.3651677","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3651677","url":null,"abstract":"This article proposes a resilient control framework for securing cyber-physical systems (CPSs), specifically addressing nonlinear descriptor systems operating under communication constraints and subject to sensor and actuator attacks. We integrate Takagi-Sugeno (T-S) fuzzy models with a Q-learning-based event-triggered mechanism (ETM) and adopt a sliding-mode control strategy to establish a resilient security architecture that adaptively balances operational efficiency with robust protection against cyber-physical threats. A major contribution of this work lies in designing an adaptive fuzzy sliding-mode observer (SMO) with mismatched premise variables for the estimation of compromised system states. Additionally, a sliding-mode controller (SMC) is synthesized to maintain closed-loop admissibility and ensure the reachability of sliding surfaces. We advance beyond the existing approaches by employing the secretary bird optimization algorithm (SBOA) to optimize controller and observer gains, thereby solving the nonconvex optimization challenges present in controller and observer design. The effectiveness of the proposed method is validated through extensive Monte Carlo simulations on a truck-trailer system. These simulations demonstrate the efficacy of the approach in maintaining system stability and performance under various attack scenarios, thereby making a significant contribution to the security of nonlinear systems in networked environments.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"62 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015431","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 : 2026-01-21DOI: 10.1109/tcyb.2026.3650767
Wendi Chen,Ben Niu,Xudong Zhao,Ding Wang
This article investigates the adaptive tracking control strategy for a class of nonlinear systems subjected to false data injection (FDI) attacks, incorporating an improved event-triggered mechanism. A significant breakthrough of this study lies in the challenge that, after FDI, not all states of the system can be utilized for stability design, thereby making it more complicated to achieve tracking control. This article eliminates the restrictive assumption, required in some existing results, that the attack signal at the first step must be known. Instead, we propose to estimate the tracking error directly. This approach not only facilitates the tracking control of nonlinear systems but also enhances the generalizability and practical applicability of the solution. To conserve system resources, an improved event-triggered condition is proposed that utilizes the triggered attacked-output. Consequently, the controllers and adaptive laws are implemented using the sampled states rather than continuous real-time states, thereby minimizing unnecessary computations and communications. By constructing Lyapunov functions, the proposed control strategy ensures that all signals in the closed-loop system are globally bounded. Finally, the simulation results are displayed to validate the effectiveness of the proposed control strategy.
{"title":"Adaptive Tracking Control for Nonlinear Systems Under False Data Injection Attacks via Intermittent State Triggering.","authors":"Wendi Chen,Ben Niu,Xudong Zhao,Ding Wang","doi":"10.1109/tcyb.2026.3650767","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3650767","url":null,"abstract":"This article investigates the adaptive tracking control strategy for a class of nonlinear systems subjected to false data injection (FDI) attacks, incorporating an improved event-triggered mechanism. A significant breakthrough of this study lies in the challenge that, after FDI, not all states of the system can be utilized for stability design, thereby making it more complicated to achieve tracking control. This article eliminates the restrictive assumption, required in some existing results, that the attack signal at the first step must be known. Instead, we propose to estimate the tracking error directly. This approach not only facilitates the tracking control of nonlinear systems but also enhances the generalizability and practical applicability of the solution. To conserve system resources, an improved event-triggered condition is proposed that utilizes the triggered attacked-output. Consequently, the controllers and adaptive laws are implemented using the sampled states rather than continuous real-time states, thereby minimizing unnecessary computations and communications. By constructing Lyapunov functions, the proposed control strategy ensures that all signals in the closed-loop system are globally bounded. Finally, the simulation results are displayed to validate the effectiveness of the proposed control strategy.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"47 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015298","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 studies the 3-D dynamic rendezvous control problem for coordinated heterogeneous marine vehicles, including an uncrewed underwater vehicle (UUV) and an autonomous surface vehicle (ASV). An observer-based safety-preserving rendezvous control approach is proposed to robustly stabilize the rendezvous errors under the port-Hamiltonian (PH) framework. First, an interconnection and damping assignment passivity-based control (IDA-PBC) method is adopted to provide a basic stabilizing control framework. In this problem, both vehicles are faced with hydrodynamic model uncertainties and unknown external disturbances. Then, to preserve the rendezvous safety under uncertain dynamics, the prescribed performance control (PPC) transformation is implemented for the ascending motion to get the equivalent approaching-constrained PH system. The intuitive design procedure provided by the IDA-PBC method, along with the collision-free rendezvous safety guaranteed by the auxiliary PPC technique, reduces the controller design complexity while providing a smooth rendezvous trajectory. Besides, a structure-keeping uncertainty observer algorithm is designed and incorporated to simultaneously handle model uncertainties and environmental disturbances without destroying the interconnection structure. Under the proposed approach, the UUV-ASV rendezvous errors can be effectively stabilized with rigorous closed-loop stability analysis. Finally, both simulations and comparative experiments are conducted to demonstrate the effectiveness and advantages of the proposed approach.
{"title":"Robust Safety-Preserving Rendezvous Control for Coordinated Heterogeneous Marine Vehicles: An Observer-Based Structure-Keeping Port-Hamiltonian Approach.","authors":"Zehua Jia,Huahuan Wang,Wentao Wu,Guoqing Zhang,Weidong Zhang","doi":"10.1109/tcyb.2026.3652215","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3652215","url":null,"abstract":"This article studies the 3-D dynamic rendezvous control problem for coordinated heterogeneous marine vehicles, including an uncrewed underwater vehicle (UUV) and an autonomous surface vehicle (ASV). An observer-based safety-preserving rendezvous control approach is proposed to robustly stabilize the rendezvous errors under the port-Hamiltonian (PH) framework. First, an interconnection and damping assignment passivity-based control (IDA-PBC) method is adopted to provide a basic stabilizing control framework. In this problem, both vehicles are faced with hydrodynamic model uncertainties and unknown external disturbances. Then, to preserve the rendezvous safety under uncertain dynamics, the prescribed performance control (PPC) transformation is implemented for the ascending motion to get the equivalent approaching-constrained PH system. The intuitive design procedure provided by the IDA-PBC method, along with the collision-free rendezvous safety guaranteed by the auxiliary PPC technique, reduces the controller design complexity while providing a smooth rendezvous trajectory. Besides, a structure-keeping uncertainty observer algorithm is designed and incorporated to simultaneously handle model uncertainties and environmental disturbances without destroying the interconnection structure. Under the proposed approach, the UUV-ASV rendezvous errors can be effectively stabilized with rigorous closed-loop stability analysis. Finally, both simulations and comparative experiments are conducted to demonstrate the effectiveness and advantages of the proposed approach.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"66 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015430","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 : 2026-01-21DOI: 10.1109/tcyb.2026.3651727
Lulu Zhang,Huaguang Zhang,Tianbiao Wang,Zhijie Han
This article investigates the optimal containment control (OCC) problem of a class of nonlinear stochastic multiagent systems (MASs) under secure communication. A novel OCC strategy is designed, ensuring that all followers converge to the convex hull spanned by the leaders while maintaining secure information exchange and minimizing cost by the predefined performance function. To achieve this, an encryption and decryption mechanism is employed in the information exchange among agents, ensuring secure communication and preserving data integrity. Meanwhile, to solve the stochastic version of Hamilton-Jacobi-Bellman (HJB) equation arising in stochastic factor, a simplified adaptive dynamic programming (ADP) framework is introduced under the conditional expectation. Specifically, a single critic network weights tuning rule is developed based on the experience replay technique (ERT). The use of ERT relaxes the traditional persistence of excitation requirement. Theoretical analysis guarantees the uniform ultimate boundedness of the closed-loop system. The simulation results confirm the effectiveness of the designed OCC strategy.
{"title":"Optimal Containment Control for Stochastic Multiagent Systems via Simplified ADP Under Secure Communication.","authors":"Lulu Zhang,Huaguang Zhang,Tianbiao Wang,Zhijie Han","doi":"10.1109/tcyb.2026.3651727","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3651727","url":null,"abstract":"This article investigates the optimal containment control (OCC) problem of a class of nonlinear stochastic multiagent systems (MASs) under secure communication. A novel OCC strategy is designed, ensuring that all followers converge to the convex hull spanned by the leaders while maintaining secure information exchange and minimizing cost by the predefined performance function. To achieve this, an encryption and decryption mechanism is employed in the information exchange among agents, ensuring secure communication and preserving data integrity. Meanwhile, to solve the stochastic version of Hamilton-Jacobi-Bellman (HJB) equation arising in stochastic factor, a simplified adaptive dynamic programming (ADP) framework is introduced under the conditional expectation. Specifically, a single critic network weights tuning rule is developed based on the experience replay technique (ERT). The use of ERT relaxes the traditional persistence of excitation requirement. Theoretical analysis guarantees the uniform ultimate boundedness of the closed-loop system. The simulation results confirm the effectiveness of the designed OCC strategy.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"85 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015299","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}
Few-shot anomaly detection (FSAD) has emerged as a critical paradigm for identifying irregularities using scarce normal references. While recent methods have integrated textual semantics to complement visual data, they predominantly rely on features pretrained on natural scenes, thereby neglecting the granular, domain-specific semantics essential for industrial inspection. Furthermore, prevalent fusion strategies often resort to superficial concatenation, failing to address the inherent semantic misalignment between visual and textual modalities, which compromises robustness against cross-modal interference. To bridge these gaps, this study proposes VTFusion, a vision-text multimodal fusion framework tailored for FSAD. The framework rests on two core designs. First, adaptive feature extractors for both image and text modalities are introduced to learn task-specific representations, bridging the domain gap between pretrained models and industrial data; this is further augmented by generating diverse synthetic anomalies to enhance feature discriminability. Second, a dedicated multimodal prediction fusion module is developed, comprising a fusion block that facilitates rich cross-modal information exchange and a segmentation network that generates refined pixel-level anomaly maps under multimodal guidance. VTFusion significantly advances FSAD performance, achieving image-level area under the receiver operating characteristics (AUROCs) of 96.8% and 86.2% in the 2-shot scenario on the MVTec AD and VisA datasets, respectively. Furthermore, VTFusion achieves an AUPRO of 93.5% on a real-world dataset of industrial automotive plastic parts introduced in this article, further demonstrating its practical applicability in demanding industrial scenarios.
{"title":"VTFusion: A Vision-Text Multimodal Fusion Network for Few-Shot Anomaly Detection.","authors":"Yuxin Jiang,Yunkang Cao,Yuqi Cheng,Yiheng Zhang,Weiming Shen","doi":"10.1109/tcyb.2026.3651630","DOIUrl":"https://doi.org/10.1109/tcyb.2026.3651630","url":null,"abstract":"Few-shot anomaly detection (FSAD) has emerged as a critical paradigm for identifying irregularities using scarce normal references. While recent methods have integrated textual semantics to complement visual data, they predominantly rely on features pretrained on natural scenes, thereby neglecting the granular, domain-specific semantics essential for industrial inspection. Furthermore, prevalent fusion strategies often resort to superficial concatenation, failing to address the inherent semantic misalignment between visual and textual modalities, which compromises robustness against cross-modal interference. To bridge these gaps, this study proposes VTFusion, a vision-text multimodal fusion framework tailored for FSAD. The framework rests on two core designs. First, adaptive feature extractors for both image and text modalities are introduced to learn task-specific representations, bridging the domain gap between pretrained models and industrial data; this is further augmented by generating diverse synthetic anomalies to enhance feature discriminability. Second, a dedicated multimodal prediction fusion module is developed, comprising a fusion block that facilitates rich cross-modal information exchange and a segmentation network that generates refined pixel-level anomaly maps under multimodal guidance. VTFusion significantly advances FSAD performance, achieving image-level area under the receiver operating characteristics (AUROCs) of 96.8% and 86.2% in the 2-shot scenario on the MVTec AD and VisA datasets, respectively. Furthermore, VTFusion achieves an AUPRO of 93.5% on a real-world dataset of industrial automotive plastic parts introduced in this article, further demonstrating its practical applicability in demanding industrial scenarios.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"263 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015297","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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