{"title":"Observer-Based Bounded H<sub>∞</sub> Control for Shift-Varying Linear Repetitive Processes With Constrained Bit Rates Over a Finite Horizon.","authors":"Chengyu Yang, Jinling Liang","doi":"10.1109/TCYB.2025.3546704","DOIUrl":"10.1109/TCYB.2025.3546704","url":null,"abstract":"<p><p>This technical correspondence examines the issue of observer-based bounded H<sub>∞</sub> control for a kind of shift-varying linear repetitive process (LRP) over networks with constrained bit rates in the finite horizon. Unlike the previous researches that address (or avoid) the problem of limited network resources by designing different scheduling protocols, this study focuses on further reducing and optimizing the bandwidth utilization by introducing a bit rate constraint model. Thus, an encoding-decoding mechanism under the constrained bit rates is proposed based on the quantization method. In order to analyze the H<sub>∞</sub> performance of the LRP and design an appropriate controller, the LRP is transformed into a shift-varying two-dimensional (2-D) Fornasini-Marchesini model. Sufficient conditions in recursive linear matrix inequalities are proposed to ensure that the extended system achieves a bounded H<sub>∞</sub> performance over a finite horizon within the 2-D framework. Furthermore, a component-based strategy for allocating the bit rates is provided to expand the quantization region under the constraint of bit rates. Finally, the effectiveness of the proposed method is verified by a simulation example.</p>","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657080","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}
Qifang Liu, Jianliang Mao, Linyan Han, Chuanlin Zhang, Jun Yang
{"title":"Predictive Observer-Based Dual-Rate Prescribed Performance Control for Visual Servoing of Robot Manipulators With View Constraints.","authors":"Qifang Liu, Jianliang Mao, Linyan Han, Chuanlin Zhang, Jun Yang","doi":"10.1109/TCYB.2025.3546800","DOIUrl":"10.1109/TCYB.2025.3546800","url":null,"abstract":"<p><p>This article simultaneously addresses the dual-rate and view constraints issues for the image-based visual servoing (IBVS) system of robot manipulators. Considering the low sampling bandwidth of the camera, potentially diminishing the efficiency of the robotic controller in updating low-level servoing control commands, a predictive observer (PO) is initially designed to forecast the system output during the high-level sampling intervals. Moreover, by leveraging a mixture of soft-sensing and real-measured signals, a dual-rate integral-based prescribed performance control (DRIPPC) approach is devised. The benefit lies in that the proposed control method samples the low-frequency state signal while generating a relatively high-frequency control action, ensuring rapid response of the robot manipulator while maintaining strict adherence to field-of-view (FOV) constraints. Finally, the effectiveness of the proposed control approach is validated through a series of experiments conducted on a Universal Robots 5 (UR5) manipulator.</p>","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630244","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}
{"title":"Data-Driven Inverse Reinforcement Learning for Heterogeneous Optimal Robust Formation Control.","authors":"Fatemeh Mahdavi Golmisheh, Saeed Shamaghdari","doi":"10.1109/TCYB.2025.3546563","DOIUrl":"10.1109/TCYB.2025.3546563","url":null,"abstract":"<p><p>This article presents novel data-driven inverse reinforcement learning (IRL) algorithms to optimally address heterogeneous formation control problems in the presence of disturbances. We propose expert-estimator-learner multiagent systems (MASs) as independent systems with similar interaction graphs. First, a model-based IRL algorithm is introduced for the estimator MAS to determine its optimal control and reward functions. Using the estimator IRL algorithm results, a robust algorithm for model-free IRL is presented to reconstruct the learner MAS's optimal control and reward functions without knowing the learners' dynamics. Therefore, estimator MAS aims to estimate experts' desired formation and learner MAS wants to track the estimators' trajectories optimally. As a final step, data-driven implementations of these proposed IRL algorithms are presented. Consequently, this research contributes to identifying unknown reward functions and optimal controls by conducting demonstrations. Our analysis shows that the stability and convergence of MASs are thoroughly ensured. The effectiveness of the given algorithms is demonstrated via simulation results.</p>","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630072","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}
Yun Liu, Wen Yang, Chun-Yi Su, Yue Luo, Xiaofan Wang
{"title":"Observer-Based Control of Networked Periodic Piecewise Systems With Encoding–Decoding Mechanism","authors":"Yun Liu, Wen Yang, Chun-Yi Su, Yue Luo, Xiaofan Wang","doi":"10.1109/tcyb.2025.3543878","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3543878","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"26 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608062","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}
{"title":"Robust Model Predictive Control of a Gait Rehabilitation Exoskeleton With Whole Body Motion Planning and Neuro-Dynamics Optimization","authors":"Liangrui Xu, Zhijun Li, Guoxin Li, Lingjing Jin","doi":"10.1109/tcyb.2025.3545064","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3545064","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"23 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143598820","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}
Zhirong Zhang, Yongduan Song, Xiaoyuan Zheng, Long Chen, Petros Ioannou
{"title":"Observer-Based Decentralized Adaptive Control of Interconnected Nonlinear Systems With Output/Input Triggering","authors":"Zhirong Zhang, Yongduan Song, Xiaoyuan Zheng, Long Chen, Petros Ioannou","doi":"10.1109/tcyb.2025.3545279","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3545279","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"56 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143598854","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}
{"title":"Adaptive Predefined Time Control for Stochastic Switched Nonlinear Systems With Full-State Error Constraints and Input Quantization.","authors":"Yu Yang, Shuai Sui, Tengfei Liu, C L Philip Chen","doi":"10.1109/TCYB.2025.3531381","DOIUrl":"https://doi.org/10.1109/TCYB.2025.3531381","url":null,"abstract":"<p><p>A neural network adaptive quantized predefined-time control problem is studied for switching stochastic nonlinear systems with full-state error constraints under arbitrary switching. Unlike previous research on rapid convergence, the predefined-time stability criteria are introduced and established for stochastic nonlinear systems, ensuring the stabilization of the control system within a specified time frame. The chattering issue is avoided and it is split into two limited nonlinear functions using a hysteresis quantizer. To address the full-state error constraint problem, a universal barrier Lyapunov function is presented. The common Lyapunov function approach is used to demonstrate the stability of controlled systems. The results demonstrate that the proposed control method ensures all closed-loop signals are probabilistically practically predefined time-stabilized (PPTS), with the system output closely tracking the specified reference signal. Finally, simulated examples validate the effectiveness of the suggested control technique.</p>","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596794","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}