IEEE Transactions on Systems Man Cybernetics-Systems最新文献_第5页

Neuro-Adaptive Fault-Tolerant Attitude Control of a Quadrotor UAV With Flight Envelope Limitation and Feedforward Compensation

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-26 DOI: 10.1109/TSMC.2025.3534986

Yan-Jun Liu;Benke Gao;Dengxiu Yu;Dapeng Li;Lei Liu

引用次数: 0

Reinforcement-Learning-Based Counter Deception for Nonlinear Pursuit–Evasion Game With Incomplete and Asymmetric Information

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-26 DOI: 10.1109/TSMC.2025.3541105

Yongkang Wang;Rongxin Cui;Weisheng Yan;Xinxin Guo;Shouxu Zhang;Zhuo Zhang;Zhexuan Zhao

{"title":"Reinforcement-Learning-Based Counter Deception for Nonlinear Pursuit–Evasion Game With Incomplete and Asymmetric Information","authors":"Yongkang Wang;Rongxin Cui;Weisheng Yan;Xinxin Guo;Shouxu Zhang;Zhuo Zhang;Zhexuan Zhao","doi":"10.1109/TSMC.2025.3541105","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3541105","url":null,"abstract":"In this article, we investigate the problem of capturing a noncooperative target with deception behavior using reinforcement learning (RL) under incomplete information. The pursuer copes not only with its maneuverability constraint but also with the target’s deception behavior, in which the target deliberately conceals its private preference information. The target capture game involving deception behavior is formulated as a nonlinear differential game framework where the information structure is incomplete and asymmetric. The solution to this differential game is proposed based on an RL policy that incorporates critic, actor, and virtual actor neural networks (NNs), when taking into consideration the maneuverability constraint and information structure of the pursuer. Moreover, the states of the constrained adversarial system and the weight errors are proven to be ultimately uniformly bounded (UUB). To counter the deception of the target, we adopt unscented Kalman filter (UKF) to obtain the target intention on energy preference, and integrate it into the pursuer strategy. The feasibility of the proposed strategy and its superiority are verified through comparisons with recent works.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3261-3274"},"PeriodicalIF":8.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hierarchical Learning-Based Integrated Robust Optimal Control for Nonlinear Systems

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3538841

Jiacheng Zhang;Jingjing Wang;Honggui Han;Ying Hou;Yanting Huang

{"title":"Hierarchical Learning-Based Integrated Robust Optimal Control for Nonlinear Systems","authors":"Jiacheng Zhang;Jingjing Wang;Honggui Han;Ying Hou;Yanting Huang","doi":"10.1109/TSMC.2025.3538841","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3538841","url":null,"abstract":"The optimal control of nonlinear systems is crucial to improve system performance. However, the uncertainties of cost functions and systems dynamics make it difficult to solve the optimal control laws. To cope with this problem, a hierarchical learning-based integrated robust optimal control (HL-IROC) method is proposed in this article. The merits of the proposed HL-IROC method are three aspects: First, a hierarchical learning-based integrated optimal control (HL-IOC) scheme, contains a system dynamic learning layer and a cost function learning layer, is designed to transform the original optimal control problem into an integrated optimization problem with control laws as decision variables. Then, the relationships between cost functions and control laws are captured to overcome the difficulties brought by uncertainties in the optimal control process. Second, a global-local cooperative robust evolutionary optimization (GL-CREO) algorithm is proposed to obtain the optimal control laws. Then, a global-local robust searching strategy is employed to deal with two types of uncertainties for improving the robustness of control laws. Third, the convergence analysis of HL-IOC and GL-CREO is discussed in theory. In the experiments, the effectiveness of HL-IROC is illustrated with a nonlinear system and a wastewater treatment process.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3119-3129"},"PeriodicalIF":8.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy Adaptive Predefined Time Control With Global Prescribed Performance for Robotic Manipulator Under Unknown Disturbance

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3540777

Chengguo Liu;Kai Zhao;Junyang Li;Chenguang Yang

{"title":"Fuzzy Adaptive Predefined Time Control With Global Prescribed Performance for Robotic Manipulator Under Unknown Disturbance","authors":"Chengguo Liu;Kai Zhao;Junyang Li;Chenguang Yang","doi":"10.1109/TSMC.2025.3540777","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540777","url":null,"abstract":"The assurance of faster transient response rate, higher steady-state tracking accuracy, and global adaptability are crucial for enhancing the efficiency and robustness of manipulators during operation. This article explores a novel fuzzy adaptive predefined-time controller based on global prescribed performance for robotic systems with unknown dynamics and bounded disturbances. First, a predefined time error transformation function (PTETF) is developed and combined with a barrier function based on constant value constraints for control design, which not only significantly simplifies the derivation process of the proposed predefined time prescribed performance control (PTPPC), but also equips it with the ability of global constraints on the trajectory tracking error. Then, we utilize the fuzzy logic system (FLS) with a single-parameter update mechanism to compensate for the dynamic uncertainty of manipulators, thereby reducing computational complexity and cost. In addition, a fixed time disturbance observer (FxTDOB) is introduced to alleviate the effect of nonparametric disturbances on the tracking performance. Further, by integrating the predefined time theory with Lyapunov method to ensure that all state signals of the controlled system converge in a predefined time. Finally, numerical simulations and practical experiments are carried out to demonstrate the effectiveness of the proposed framework.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3397-3410"},"PeriodicalIF":8.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Tracking Control for Leader-Following Consensus of Nonlinear Multiagent Systems

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3539351

Wei Su;Chaoxu Mu;Xiong Yang;Jinshan Bian;Changyin Sun

{"title":"Optimal Tracking Control for Leader-Following Consensus of Nonlinear Multiagent Systems","authors":"Wei Su;Chaoxu Mu;Xiong Yang;Jinshan Bian;Changyin Sun","doi":"10.1109/TSMC.2025.3539351","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3539351","url":null,"abstract":"This article investigates distributed adaptive leader-following consensus tracking optimal control problem for nonlinear multiagent systems (MASs) subject to unknown nonlinearities and uncertain external disturbances. In contrast to traditional centralized control, the primary challenge is that only partial subsystems can access the desired reference trajectory. To address this, positive time-varying smooth function compensating terms are introduced to counteract the effects of uncertain external disturbances and unknown desired trajectories. Then, by fusing consensus errors into the backstepping technique, feedforward controllers are given. On this basis, the controlled nonlinear systems are transformed into an equivalent affine form, and feedback optimal controllers are designed using actor and critic neural networks (NNs) to execute control behavior and evaluate control performance. The whole control laws comprise both feedforward and feedback controllers. The proposed distributed adaptive consensus control protocol can simultaneously achieve desired optimal control performance and minimize the cost function, as demonstrated through theoretical analysis and simulation results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3098-3107"},"PeriodicalIF":8.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy-Model-Based Robust Fault Estimation Observer Design for Nonlinear Discrete-Time Systems Using Dissipativity Theory

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2023.3332672

Yunfei Mu;Huaguang Zhang;Weihua Li;Kun Zhang

{"title":"Fuzzy-Model-Based Robust Fault Estimation Observer Design for Nonlinear Discrete-Time Systems Using Dissipativity Theory","authors":"Yunfei Mu;Huaguang Zhang;Weihua Li;Kun Zhang","doi":"10.1109/TSMC.2023.3332672","DOIUrl":"https://doi.org/10.1109/TSMC.2023.3332672","url":null,"abstract":"This article investigates the robust fault estimation (FE) scheme for a class of discrete-time nonlinear dynamics subject to simultaneous bounded disturbances, sensor and actuator/process faults through the T–S fuzzy method. By constructing an augmented system that contains sensor faults as part of its state, a dissipativity-based FE observer is proposed to achieve sensor and actuator/process faults reconstruction. Combine with the fuzzy Lyapunov function method and dissipativity theory, some brand-new conditions with slack scalars and matrices are attained to ensure that observation error systems are strictly <inline-formula> <tex-math>$(mathcal {R},mathcal {W},mathcal {S}) -delta -$ </tex-math></inline-formula>dissipative. Besides, to improve the transient FE performance, regional pole placement problem is also considered in FE observer design. It is worth mentioning that different from some existing results which assume that actuator faults occur in a constant form, the method given in this article is suitable for more types of faults such as time-varying ones. By two simulation experiments, the validity and practicability of the proposed FE observer are fully illustrated.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3076-3085"},"PeriodicalIF":8.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Predefined-Time Bounded Consensus Tracking Control of Multiagent Systems Under Input/Output Quantization

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3540109

Tao Jiang;Yan Yan;Shuzhi Sam Ge

引用次数: 0

Integrated Guidance and Control of Morphing Flight Vehicle via Sliding-Mode-Based Robust Reinforcement Learning 通过基于滑动模式的鲁棒强化学习实现变形飞行器的综合制导与控制

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3540262

Chengyu Cao;Fanbiao Li;Qichao Xie;Yuxin Liao;Tingwen Huang;Chunhua Yang;Weihua Gui

{"title":"Integrated Guidance and Control of Morphing Flight Vehicle via Sliding-Mode-Based Robust Reinforcement Learning","authors":"Chengyu Cao;Fanbiao Li;Qichao Xie;Yuxin Liao;Tingwen Huang;Chunhua Yang;Weihua Gui","doi":"10.1109/TSMC.2025.3540262","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540262","url":null,"abstract":"This article introduces an integrated guidance and control method for morphing flight vehicles, addressing model uncertainties and external disturbances through a robust deep reinforcement learning framework built on sliding-mode control (SMC). The method development begins with the establishment of a longitudinal guidance and control model and a detailed introduction to the necessary theoretical foundations. The proposed approach incorporates robust observation strategies enabled by a novel fixed-time SMC design. The agent’s actions, rewards, neural network structure, and training process are meticulously crafted to tackle practical guidance and control challenges effectively. Trained offline to achieve seamless integration of position and attitude control, the agent generates end-to-end control commands in real time during online operation. Extensive testing, including robustness evaluations, generalization assessments, and comparative performance analyses, demonstrates the superiority and reliability of the proposed method.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3350-3362"},"PeriodicalIF":8.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predefined-Time Distributed Fault-Tolerant Control for Nonlinear Multiagent Systems Suffering From Nonaffine Faults

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-25 DOI: 10.1109/TSMC.2025.3540464

Shuai Cheng;Bin Xin;Jie Chen;Fang Deng

引用次数: 0

Curve-Suppression-Based Event-Triggered Mechanisms for Quasi-Synchronization of Fuzzy Delayed Neural Networks on Time Scales

IF 8.6 1区计算机科学

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-02-24 DOI: 10.1109/TSMC.2025.3540092

Peng Wan;Yufeng Zhou;Zhigang Zeng;Jingang Lai

{"title":"Curve-Suppression-Based Event-Triggered Mechanisms for Quasi-Synchronization of Fuzzy Delayed Neural Networks on Time Scales","authors":"Peng Wan;Yufeng Zhou;Zhigang Zeng;Jingang Lai","doi":"10.1109/TSMC.2025.3540092","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3540092","url":null,"abstract":"The vast majority of published event-triggered mechanisms (ETMs) are constructed based on measurement errors, which introduces a problem naturally that they are updated when the measurement errors exceed the thresholds although the current obtained sampling states can make systems converge well. With this problem in mind, we redesign ETMs for quasi-synchronization of T-S fuzzy neural networks (FNNs) with time delays on time scales. First, a novel ETM is designed for continuous-time FNNs with time-varying delays to achieve quasi-synchronization, with which synchronization errors is suppressed to globally exponentially converge to a ball. Second, we introduce the ETM for continuous-time FNNs to discrete-time FNNs, owing to the existence of discrete-time states, the Lypunov function of synchronization errors run over the exponentially decay curve, but it can be suppressed to evolve under another exponentially decay curve. Third, for FNNs on time scales with constant and time-varying delays, we estimate the forward jump operator of the Lyapunov functions and design ETMs to guarantee that the Lypunov functions evolve under the exponentially decay curves, so quasi-synchronization can be achieved. Last but not least, we prove that Zeno behavior will not happen and four numerical examples are introduced to verify the validity and the superiority of the proposed ETMs in reducing information transmission.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 5","pages":"3174-3187"},"PeriodicalIF":8.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0