International Journal of Robust and Nonlinear Control最新文献

Affine Formation Control for End-Effectors of Networked Manipulators With Maneuvering Leaders and Unknown System Parameters 具有机动先导和未知系统参数的网络化机械臂末端执行器仿射编队控制

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-14 DOI: 10.1002/rnc.70379

Yichao Ao, Qifeng Zhang, Yingmin Jia, Yang Liu

{"title":"Affine Formation Control for End-Effectors of Networked Manipulators With Maneuvering Leaders and Unknown System Parameters","authors":"Yichao Ao, Qifeng Zhang, Yingmin Jia, Yang Liu","doi":"10.1002/rnc.70379","DOIUrl":"https://doi.org/10.1002/rnc.70379","url":null,"abstract":"<div>\u0000 \u0000 <p>This article studies the distributed control problem of collectively achieving and maneuvering the formation shape for the end-effectors of networked multiple Euler-Lagrange manipulators. In the formation process, precious few manipulators, called leaders, determine their motions autonomously, whereas a bulk of followers steer themselves to form the target geometric pattern and achieve desired affine transformation. For both undirected and directed graphs, distributed control protocols are proposed to achieve formation in the task space, but through the control inputs injected at joints' level, without using the absolute positions of the end-effectors. Meanwhile, distributed observers and adaptive laws are designed for each follower to estimate its desired behavior and both dynamic and kinematic unknown parameters. Moreover, a new kinematic adaptive law is proposed for undirected graph without using absolute velocity information. The asymptotic convergence of the closed-loop systems is proven, and the effectiveness of the proposed approach is validated by exemplary simulation examples of networked two-link manipulators.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3838-3854"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Asynchronous State Estimation for Markov Jump Neural Networks Under Complex Transition Probabilities: A Dynamic Event-Based Weighted Try-Once-Discard Protocol 复杂转移概率下马尔可夫跳跃神经网络的异步状态估计：一种基于动态事件的加权“尝试一次丢弃”协议

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-18 DOI: 10.1002/rnc.70378

Yaxiao Guo, Dongdong Ren, Feng Li, Lei Su, Junmin Li

{"title":"Asynchronous State Estimation for Markov Jump Neural Networks Under Complex Transition Probabilities: A Dynamic Event-Based Weighted Try-Once-Discard Protocol","authors":"Yaxiao Guo, Dongdong Ren, Feng Li, Lei Su, Junmin Li","doi":"10.1002/rnc.70378","DOIUrl":"https://doi.org/10.1002/rnc.70378","url":null,"abstract":"<div>\u0000 \u0000 <p>This work focuses on the state estimation for hidden markov jump neural networks (MJNNs) under complex transition probabilities (C-TPs) and network-induced communication constraints. Obtaining precise transition probabilities (TPs) of a markov process is often challenging in practical scenarios. Therefore, this work considers the TPs may be unknown or imprecise, leading to the C-TPs situations, which are more practical for MJNNs. In order to save network resources and reduce data conflicts, a novel dynamic event-based weighted try-once-discard (DEWTOD) protocol is introduced. Unlike existing protocols, the DEWTOD protocol simultaneously determines the sampling instant and the node responsible for transmission. To accurately reflect the asynchronous phenomenon between the system and the estimator, this paper proposes a nonhomogeneous hidden Markov model, which the detection transition matrix is time-dependent and is characterized by a collection of polyhedra. Through a polytopic-structured Lyapunov function, some sufficient conditions are established to ensure mean-square exponential stability of the augmented systems. To this end, two examples are presented to demonstrate the effectiveness of the proposed estimator design method.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3937-3948"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Network Functional Observer-Based Composite Anti-Disturbance Control for Systems With Multiplicative and Implicit Disturbances 基于神经网络功能观测器的乘式和隐式扰动系统复合抗干扰控制

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-19 DOI: 10.1002/rnc.70334

Baopeng Zhu, Yu Wang, Yangyang Cui, Yukai Zhu

{"title":"Neural Network Functional Observer-Based Composite Anti-Disturbance Control for Systems With Multiplicative and Implicit Disturbances","authors":"Baopeng Zhu, Yu Wang, Yangyang Cui, Yukai Zhu","doi":"10.1002/rnc.70334","DOIUrl":"https://doi.org/10.1002/rnc.70334","url":null,"abstract":"<div>\u0000 \u0000 <p>High precision control under disturbances and uncertainties is critical to the safe, stable, and long-term continuous operation of the system. In this paper, a composite anti-disturbance control strategy for systems affected by both multiplicative and implicit disturbances is proposed. First, a reduced neural network functional observer is developed to estimate the partially unknown states and the implicit disturbances, which takes into account the effect of the multiplicative disturbances and the uncertainties in the implicit disturbances, both of which are related to the system's states. The neural network is employed for approximating the multiplicative disturbances. Then, a dynamic sliding mode surface with disturbance compensation is introduced to ensure exponential convergence of systems with the multiplicative disturbances and the implicit disturbances. Furthermore, a novel barrier function-based adaptive sliding mode control law is designed to guarantee that the system trajectories reach the sliding surface, which greatly reduces chattering without requiring prior knowledge of the upper bound on system uncertainties. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed approach.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3923-3936"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-Driven Fixed-Time Cooperative Attitude Control of High-Speed Unmanned System Considering Input Saturation and Actuator Failure 考虑输入饱和和执行器失效的高速无人系统事件驱动固定时间协同姿态控制

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-19 DOI: 10.1002/rnc.70393

Xin Ning, Xuyang Wang, Zheng Wang, Yi Wang, Caisheng Wei

引用次数: 0

Asynchronous State Estimation for Markov Jump Neural Networks Under Complex Transition Probabilities: A Dynamic Event-Based Weighted Try-Once-Discard Protocol 复杂转移概率下马尔可夫跳跃神经网络的异步状态估计：一种基于动态事件的加权“尝试一次丢弃”协议

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-18 DOI: 10.1002/rnc.70378

Yaxiao Guo, Dongdong Ren, Feng Li, Lei Su, Junmin Li

{"title":"Asynchronous State Estimation for Markov Jump Neural Networks Under Complex Transition Probabilities: A Dynamic Event-Based Weighted Try-Once-Discard Protocol","authors":"Yaxiao Guo, Dongdong Ren, Feng Li, Lei Su, Junmin Li","doi":"10.1002/rnc.70378","DOIUrl":"https://doi.org/10.1002/rnc.70378","url":null,"abstract":"<div>\u0000 \u0000 <p>This work focuses on the state estimation for hidden markov jump neural networks (MJNNs) under complex transition probabilities (C-TPs) and network-induced communication constraints. Obtaining precise transition probabilities (TPs) of a markov process is often challenging in practical scenarios. Therefore, this work considers the TPs may be unknown or imprecise, leading to the C-TPs situations, which are more practical for MJNNs. In order to save network resources and reduce data conflicts, a novel dynamic event-based weighted try-once-discard (DEWTOD) protocol is introduced. Unlike existing protocols, the DEWTOD protocol simultaneously determines the sampling instant and the node responsible for transmission. To accurately reflect the asynchronous phenomenon between the system and the estimator, this paper proposes a nonhomogeneous hidden Markov model, which the detection transition matrix is time-dependent and is characterized by a collection of polyhedra. Through a polytopic-structured Lyapunov function, some sufficient conditions are established to ensure mean-square exponential stability of the augmented systems. To this end, two examples are presented to demonstrate the effectiveness of the proposed estimator design method.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3937-3948"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite-Time Synchronization of PDT Switched Stochastic Neural Networks under Event-Triggered Mechanism 事件触发机制下PDT切换随机神经网络的有限时间同步

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-21 DOI: 10.1002/rnc.70395

Bo Liu, Yong Chen, Longsuo Li

{"title":"Finite-Time Synchronization of PDT Switched Stochastic Neural Networks under Event-Triggered Mechanism","authors":"Bo Liu, Yong Chen, Longsuo Li","doi":"10.1002/rnc.70395","DOIUrl":"https://doi.org/10.1002/rnc.70395","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the finite-time synchronization problem of master-slave stochastic neural network systems with switching signals. First, to improve resource utilization, an event-triggered mechanism is introduced, taking into account the transmission delay in the communication process, and a master-slave synchronization error system is established. Second, to overcome the limitations of traditional switching signals, a more versatile persistent dwell-time switching rule is adopted. By constructing appropriate Lyapunov–Krasovskii functionals combined with free-weight matrix methodology, sufficient conditions for the finite-time <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mi>ℋ</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mi>∞</mi>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {mathscr{H}}_{infty } $$</annotation>\u0000 </semantics></math> synchronization of the master-slave system are derived. Based on these, the controller expression is obtained via the singular value decomposition lemma. Finally, the effectiveness of the proposed method is verified through simulation examples.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"4002-4013"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Intelligent Pump Fault Diagnosis Hinges on Cross-Domain Attentional Bias Diagnosis Transfer Learning Network 基于跨域注意偏差诊断迁移学习网络的智能泵故障诊断研究

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-21 DOI: 10.1002/rnc.70353

Wenpu Wang, Jiqiu Li, Changwei Su, Yuqing Li, Shaoqing Yan, Haifeng Zhang

{"title":"Research on Intelligent Pump Fault Diagnosis Hinges on Cross-Domain Attentional Bias Diagnosis Transfer Learning Network","authors":"Wenpu Wang, Jiqiu Li, Changwei Su, Yuqing Li, Shaoqing Yan, Haifeng Zhang","doi":"10.1002/rnc.70353","DOIUrl":"https://doi.org/10.1002/rnc.70353","url":null,"abstract":"<div>\u0000 \u0000 <p>Deep learning-based fault diagnosis is a fundamental component in pump health monitoring. However, the efficiency of feature extraction and classification in cross-domain transfer learning remains a challenge. This paper proposes a novel Cross-domain Attentional Bias Diagnosis (CABD) model to enhance training efficiency for fault identification under variable working conditions. Our key contributions include (1) integrating enhanced adversarial training with spatiotemporal invariant features for superior domain adaptation (DA); (2) constructing a feature extractor with a hybrid CNN and Bi-LSTM model equipped with an attention mechanism to improve feature space alignment; (3) employing conditional entropy-based sample weighting to optimize feature transfer, thereby improving robustness in real-world applications. Experimental results on pump datasets demonstrate that the CABD model achieves at least 10% higher accuracy with higher computational efficiency compared to single-model-based neural networks, with an outstanding diagnostic accuracy of 99.448% in transfer tasks.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3989-4001"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decentralized Control for Continuous-Time Stochastic Systems With Asymmetric Information Controllers 具有非对称信息控制器的连续时间随机系统的分散控制

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-15 DOI: 10.1002/rnc.70364

Qingyuan Qi, Qing Chang, Yue Sun

引用次数: 0

Neural Network Functional Observer-Based Composite Anti-Disturbance Control for Systems With Multiplicative and Implicit Disturbances 基于神经网络功能观测器的乘式和隐式扰动系统复合抗干扰控制

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-19 DOI: 10.1002/rnc.70334

Baopeng Zhu, Yu Wang, Yangyang Cui, Yukai Zhu

{"title":"Neural Network Functional Observer-Based Composite Anti-Disturbance Control for Systems With Multiplicative and Implicit Disturbances","authors":"Baopeng Zhu, Yu Wang, Yangyang Cui, Yukai Zhu","doi":"10.1002/rnc.70334","DOIUrl":"https://doi.org/10.1002/rnc.70334","url":null,"abstract":"<div>\u0000 \u0000 <p>High precision control under disturbances and uncertainties is critical to the safe, stable, and long-term continuous operation of the system. In this paper, a composite anti-disturbance control strategy for systems affected by both multiplicative and implicit disturbances is proposed. First, a reduced neural network functional observer is developed to estimate the partially unknown states and the implicit disturbances, which takes into account the effect of the multiplicative disturbances and the uncertainties in the implicit disturbances, both of which are related to the system's states. The neural network is employed for approximating the multiplicative disturbances. Then, a dynamic sliding mode surface with disturbance compensation is introduced to ensure exponential convergence of systems with the multiplicative disturbances and the implicit disturbances. Furthermore, a novel barrier function-based adaptive sliding mode control law is designed to guarantee that the system trajectories reach the sliding surface, which greatly reduces chattering without requiring prior knowledge of the upper bound on system uncertainties. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed approach.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3923-3936"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Multiplexed MPC With Constraint Tightening for Satellite Attitude Control and Reaction Wheel Desaturation 卫星姿态控制和反作用轮去饱和约束的鲁棒多路MPC

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-23 DOI: 10.1002/rnc.70400

Sen Yang, Keck Voon Ling, Zhenhua Wang, Jing Wang

{"title":"Robust Multiplexed MPC With Constraint Tightening for Satellite Attitude Control and Reaction Wheel Desaturation","authors":"Sen Yang, Keck Voon Ling, Zhenhua Wang, Jing Wang","doi":"10.1002/rnc.70400","DOIUrl":"https://doi.org/10.1002/rnc.70400","url":null,"abstract":"<div>\u0000 \u0000 <p>Since reaction wheels are sensitive and vulnerable devices, satellites often face significant challenges such as reaction wheel failure and angular momentum saturation during long-term operation. To address these issues, this paper proposes a multiplexed model predictive control (MMPC) method for satellites equipped with two reaction wheels and three magnetorquers, which can achieve both precise attitude control and angular momentum desaturation. Moreover, considering the presence of disturbance torques acting on satellites, the proposed MMPC algorithm is endowed with robustness through the constraint tightening approach, where the set of unknown but bounded disturbance torques is represented using zonotopes. Compared with conventional MPC algorithms that update all control variables simultaneously, the MMPC algorithm described in this paper employs asynchronous control moves on each input channel. By dividing the online optimization into smaller problems for each channel, the MMPC scheme reduces computational complexity and supports faster sampling in multivariable systems, thereby enabling quicker responses to unmeasurable disturbances. Finally, simulation results demonstrate the remarkable performance of the proposed method, including reduced computational time and improved control accuracy.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"4024-4041"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0