ISA transactions最新文献

英文中文

A spatial-temporal fusion based nonlinear causality analysis framework for root cause diagnosis of faults in nonstationary industrial processes with asymmetric distribution 基于时空融合的非对称分布非平稳工业过程故障根本原因诊断框架。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.031

Liang Ma, Yifei Peng, Kaixiang Peng

In order to ensure the product quality and safe operation of automation systems, it is very important to perform efficient and accurate root cause diagnosis of faults in industrial processes. However, some traditional methods can only be used to analyze the linear causalities, and assume that the time series meet linear Gaussian assumption and are stationary after faults occur. Due to the fault information may propagated along with the causalities among process variables, the nonstationary and asymmetric characteristics make the time series regression models poorly fit, and the accuracy of causality analysis may be affected. Inspired by the above issues, in this paper, a new spatial-temporal fusion based nonlinear causality analysis framework is proposed for root cause diagnosis of faults in nonstationary industrial processes with asymmetric distribution. In particular, the problem of causality analysis for the coexistence of stationary and nonstationary time series, as well as the coexistence of symmetrical and asymmetrical distribution time series is given more attention. Firstly, a beta distribution based variational autoencoder is constructed to extract the asymmetric features of time series in industrial processes. Subsequently, a spatial-temporal fusion adjacency matrix is introduced by fast dynamic time warping, and the spatial-temporal fusion nonlinear Granger causality analysis is performed for diagnosing the root causes of faults. Finally, two datasets from the hot rolling process are used to verify the effectiveness and performance of the proposed framework.

为了保证产品质量和自动化系统的安全运行，对工业过程中的故障进行高效、准确的根本原因诊断是非常重要的。然而，一些传统的方法只能分析线性因果关系，并假设时间序列满足线性高斯假设，并且在故障发生后是平稳的。由于故障信息可能随着过程变量之间的因果关系而传播，其非平稳性和非对称性使得时间序列回归模型拟合不佳，影响因果关系分析的准确性。受上述问题的启发，本文提出了一种新的基于时空融合的非线性因果分析框架，用于非对称分布的非平稳工业过程故障的根本原因诊断。特别是平稳与非平稳时间序列共存、对称与不对称分布时间序列共存的因果分析问题得到了更多的关注。首先，构造基于beta分布的变分自编码器，提取工业过程中时间序列的不对称特征；随后，通过快速动态时间扭曲引入时空融合邻接矩阵，进行时空融合非线性格兰杰因果分析，诊断故障根源；最后，利用热轧过程的两个数据集验证了所提框架的有效性和性能。

{"title":"A spatial-temporal fusion based nonlinear causality analysis framework for root cause diagnosis of faults in nonstationary industrial processes with asymmetric distribution","authors":"Liang Ma, Yifei Peng, Kaixiang Peng","doi":"10.1016/j.isatra.2025.11.031","DOIUrl":"10.1016/j.isatra.2025.11.031","url":null,"abstract":"<div><div>In order to ensure the product quality and safe operation of automation systems, it is very important to perform efficient and accurate root cause diagnosis of faults in industrial processes. However, some traditional methods can only be used to analyze the linear causalities, and assume that the time series meet linear Gaussian assumption and are stationary after faults occur. Due to the fault information may propagated along with the causalities among process variables, the nonstationary and asymmetric characteristics make the time series regression models poorly fit, and the accuracy of causality analysis may be affected. Inspired by the above issues, in this paper, a new spatial-temporal fusion based nonlinear causality analysis framework is proposed for root cause diagnosis of faults in nonstationary industrial processes with asymmetric distribution. In particular, the problem of causality analysis for the coexistence of stationary and nonstationary time series, as well as the coexistence of symmetrical and asymmetrical distribution time series is given more attention. Firstly, a beta distribution based variational autoencoder is constructed to extract the asymmetric features of time series in industrial processes. Subsequently, a spatial-temporal fusion adjacency matrix is introduced by fast dynamic time warping, and the spatial-temporal fusion nonlinear Granger causality analysis is performed for diagnosing the root causes of faults. Finally, two datasets from the hot rolling process are used to verify the effectiveness and performance of the proposed framework.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 305-318"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145590487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Neuroadaptive consensus learning for multi-agent systems: An incremental approach to nonstrict pure-feedback control 多智能体系统的神经自适应共识学习：一种非严格纯反馈控制的增量方法。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.025

Shuting Wang, Jinsha Li, Junmin Li

This paper investigates the distributed learning consensus control problem for nonstrict pure-feedback multi-agent systems using neural networks and an incremental adaptive mechanism. A unified adaptive learning consensus control framework is first established by integrating backstepping techniques with neural network approximation. To address the algebraic loop problem inherent in conventional approaches, we develop a neural network-based solution that simultaneously simplifies controller architecture. The proposed incremental adaptation strategy enables efficient parameter updating while significantly reducing computational overhead. Notably, the control scheme incorporates robustness analysis during the design phase to effectively resolve the complexity explosion issue. Theoretical analysis demonstrates that the distributed protocol guarantees prescribed tracking performance while ensuring the uniform boundedness of all closed-loop signals. The numerical case studies validate the effectiveness and learning capabilities of the proposed adaptive control algorithm.

利用神经网络和增量自适应机制研究了非严格纯反馈多智能体系统的分布式学习一致性控制问题。将反步技术与神经网络逼近相结合，建立了统一的自适应学习共识控制框架。为了解决传统方法中固有的代数回路问题，我们开发了一种基于神经网络的解决方案，同时简化了控制器架构。所提出的增量自适应策略能够有效地更新参数，同时显著减少计算开销。值得注意的是，该控制方案在设计阶段引入了鲁棒性分析，有效地解决了复杂性爆炸问题。理论分析表明，该分布式协议在保证所有闭环信号的均匀有界性的同时保证了规定的跟踪性能。数值算例研究验证了所提自适应控制算法的有效性和学习能力。

引用次数: 0

Observer-based group consensus tracking of hybrid multi-agent systems under adaptive event-triggered mechanism 自适应事件触发机制下混合多智能体系统基于观测器的群体共识跟踪。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.039

Huiqin Pei, Weisen Liang

The group consensus tracking of multi-agent systems has been extensively applied in the coordination of unmanned system formations. However, existing methods encounter difficulties in group consensus tracking regarding the group division for the observation cooperative correction term, the enhancement of the self-adjustment ability of tracking agents and the further optimization of communication resources. Therefore, the problem of observer-based group consensus tracking of hybrid multi-agent systems under adaptive event-triggered mechanism is studied. An improved observation strategy with global observation and observation cooperative correction term clustering is proposed. By designing adaptive gain and adaptive event-triggered consensus error, an adaptive group consensus tracking control protocol is presented. To optimize the application of communication resources, an adaptive event-triggered mechanism is designed, and the occurrence of Zeno behavior is fundamentally excluded. Lyapunov method and Barbalat’s lemma are used to prove that the system can attain group consensus tracking. Finally, the efficacy of the research results is validated by a simulation example and comparative experiments.

多智能体系统的群体共识跟踪在无人系统编队协调中得到了广泛的应用。然而，现有方法在观察合作修正期的分组、跟踪主体自我调节能力的增强以及通信资源的进一步优化等方面，在群体共识跟踪方面存在困难。因此，研究了自适应事件触发机制下混合多智能体系统基于观测器的群体共识跟踪问题。提出了一种基于全局观测和观测协同校正项聚类的改进观测策略。通过设计自适应增益和自适应事件触发一致性误差，提出了一种自适应群体一致性跟踪控制协议。为了优化通信资源的使用，设计了自适应事件触发机制，从根本上排除了芝诺行为的发生。利用Lyapunov方法和Barbalat引理证明了该系统能够实现群体共识跟踪。最后，通过仿真算例和对比实验验证了研究结果的有效性。

{"title":"Observer-based group consensus tracking of hybrid multi-agent systems under adaptive event-triggered mechanism","authors":"Huiqin Pei, Weisen Liang","doi":"10.1016/j.isatra.2025.11.039","DOIUrl":"10.1016/j.isatra.2025.11.039","url":null,"abstract":"<div><div>The group consensus tracking of multi-agent systems has been extensively applied in the coordination of unmanned system formations. However, existing methods encounter difficulties in group consensus tracking regarding the group division for the observation cooperative correction term, the enhancement of the self-adjustment ability of tracking agents and the further optimization of communication resources. Therefore, the problem of observer-based group consensus tracking of hybrid multi-agent systems under adaptive event-triggered mechanism is studied. An improved observation strategy with global observation and observation cooperative correction term clustering is proposed. By designing adaptive gain and adaptive event-triggered consensus error, an adaptive group consensus tracking control protocol is presented. To optimize the application of communication resources, an adaptive event-triggered mechanism is designed, and the occurrence of Zeno behavior is fundamentally excluded. Lyapunov method and Barbalat’s lemma are used to prove that the system can attain group consensus tracking. Finally, the efficacy of the research results is validated by a simulation example and comparative experiments.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 81-93"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145688873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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-triggered multi-agent coordination in directed graphs: An intermittent control approach 有向图中事件触发的多智能体协调：一种间歇控制方法。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.046

Wenyu Qin , Yueyong Lyu , Pengyu Wang , Guangfu Ma , Zhiyong Sun

This paper develops a communication-efficient event-triggered intermittent control strategy for multi-agent coordination in directed graphs. The proposed approach establishes a condition ensuring the existence of a minimum time interval between consecutive triggered events, meaning that the event will not be triggered immediately even if the triggering condition is satisfied. This mechanism effectively reduces the communication burden and eliminates Zeno behavior. Another key advantage is that the proposed strategy is asynchronous and aperiodic, and does not require any additional constraints on control or rest periods, thus reducing the conservatism of intermittent control strategies. Finally, both numerical simulations and physical experiments are conducted on a multi-UAV coordination platform to validate the effectiveness and practical applicability of the proposed strategy.

针对有向图中多智能体协调问题，提出了一种通信高效的事件触发间歇控制策略。所提出的方法建立了一个条件，确保在连续触发事件之间存在最小的时间间隔，这意味着即使满足触发条件，事件也不会立即触发。这种机制有效地减少了通信负担，消除了芝诺行为。另一个关键的优点是，所提出的策略是异步和非周期性的，并且不需要任何额外的控制或休息周期约束，从而降低了间歇性控制策略的保守性。最后，在多无人机协同平台上进行了数值仿真和物理实验，验证了所提策略的有效性和实用性。

引用次数: 0

Adaptive neural pseudo-inverse control for time-delay nonlinear hysteretic systems considering output constraint and its application 考虑输出约束的时滞非线性滞回系统自适应神经伪逆控制及其应用。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.043

Yuehang Liu , Xiuyu Zhang , Yue Wang

Hysteresis nonlinearities, time delays and output constraints are widely present in the practical physical systems such as motion platforms driven by smart material actuators, bionic robots and ultra-high precision machining systems, however, these factors will degrade the control performance and may even induce oscillations in the control system. To overcome the aforementioned problems, in this paper, an adaptive neural pseudo-inverse control scheme is proposed for a class of time-delay nonlinear hysteresis systems considering output constraints with the following contributions: 1) a novel butterfly-like Krasnoselskii-Pokrovskii (BKP) hysteresis model with double loops is constructed to describe the double-loop hysteresis by performing the weighted superposition of the new proposed butterfly-like KP kernel; 2) a novel adaptive pseudo-inverse control algorithm is developed to avoid the difficulty of constructing the direct double-loop inverse model; 3) a new motion control platform actuated by the flexible dielectric elastomer actuators is established to verify the effectiveness of the proposed control scheme and demonstrate its feasibility for drive control systems in soft bionic robots.

在智能材料作动器驱动的运动平台、仿生机器人和超高精度加工系统等实际物理系统中，普遍存在滞后、非线性、时滞和输出约束等问题，但这些因素会降低控制性能，甚至会引起控制系统的振荡。为了克服上述问题，本文针对一类考虑输出约束的时滞非线性滞后系统，提出了一种自适应神经网络伪逆控制方案，并有以下贡献：1)通过对新提出的类蝴蝶KP核进行加权叠加，构造了一种新的类蝴蝶Krasnoselskii-Pokrovskii （BKP）双环滞后模型来描述双环滞后；2)提出了一种新的自适应伪逆控制算法，避免了直接双环逆模型的构造困难；3)建立了一个由柔性介质弹性体作动器驱动的运动控制平台，验证了所提控制方案的有效性，并验证了其在软仿生机器人驱动控制系统中的可行性。

{"title":"Adaptive neural pseudo-inverse control for time-delay nonlinear hysteretic systems considering output constraint and its application","authors":"Yuehang Liu , Xiuyu Zhang , Yue Wang","doi":"10.1016/j.isatra.2025.11.043","DOIUrl":"10.1016/j.isatra.2025.11.043","url":null,"abstract":"<div><div>Hysteresis nonlinearities, time delays and output constraints are widely present in the practical physical systems such as motion platforms driven by smart material actuators, bionic robots and ultra-high precision machining systems, however, these factors will degrade the control performance and may even induce oscillations in the control system. To overcome the aforementioned problems, in this paper, an adaptive neural pseudo-inverse control scheme is proposed for a class of time-delay nonlinear hysteresis systems considering output constraints with the following contributions: 1) a novel butterfly-like Krasnoselskii-Pokrovskii (BKP) hysteresis model with double loops is constructed to describe the double-loop hysteresis by performing the weighted superposition of the new proposed butterfly-like KP kernel; 2) a novel adaptive pseudo-inverse control algorithm is developed to avoid the difficulty of constructing the direct double-loop inverse model; 3) a new motion control platform actuated by the flexible dielectric elastomer actuators is established to verify the effectiveness of the proposed control scheme and demonstrate its feasibility for drive control systems in soft bionic robots.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 531-542"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Boundary-locked event-triggered mechanism-based adaptive flocking control for multi-USV systems 基于边界锁定事件触发机制的多usv系统自适应群集控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.034

Yong Hao , Bo Cheng , Kuo Hu , Cheng Huang

Unmanned surface vehicle swarms (USVS), comprising multiple unmanned surface vehicles (USVs), serve as critical platforms for a wide range of demanding marine operations. However, coordinating USVS poses challenges relating to flock cohesion and communication, as well as the adverse effects of uncertainty. Within this context, this paper introduces an event-based adaptive flocking control law for USVS to address these issues. Firstly, an integrated dual-mode potential function, combining a novel artificial potential function (APF) and a directionally consistent potential function (DCPF), is designed to enhance flocking cohesion while guaranteeing connectivity. Then, a boundary-locked event-triggered (BLET) mechanism effectively reduces the communication load with computable minimum inter-event time (MIET) and maximum triggering interval time (MTIT). Finally, a reinforcement learning-based echo state network (RLESN) is incorporated to compensate for unmodeled dynamics and external disturbances, thereby significantly improving the system’s robustness. Simulation results and comparative analyses validate the effectiveness and advantages of the proposed methodology.

无人水面车辆群（USVS）由多个无人水面车辆（USVS）组成，是各种苛刻的海上作业的关键平台。然而，协调USVS带来了与羊群凝聚力和沟通有关的挑战，以及不确定性的不利影响。在此背景下，本文引入了一种基于事件的USVS自适应群集控制律来解决这些问题。首先，结合人工势函数（APF）和定向一致势函数（DCPF），设计了一种集成的双模势函数，在保证簇内聚性的同时增强簇内聚性；然后，边界锁定事件触发（BLET）机制通过可计算的最小事件间时间（MIET）和最大触发间隔时间（MTIT）有效地降低了通信负载。最后，引入基于强化学习的回声状态网络（RLESN）来补偿未建模的动力学和外部干扰，从而显著提高系统的鲁棒性。仿真结果和对比分析验证了该方法的有效性和优越性。

{"title":"Boundary-locked event-triggered mechanism-based adaptive flocking control for multi-USV systems","authors":"Yong Hao , Bo Cheng , Kuo Hu , Cheng Huang","doi":"10.1016/j.isatra.2025.11.034","DOIUrl":"10.1016/j.isatra.2025.11.034","url":null,"abstract":"<div><div>Unmanned surface vehicle swarms (USVS), comprising multiple unmanned surface vehicles (USVs), serve as critical platforms for a wide range of demanding marine operations. However, coordinating USVS poses challenges relating to flock cohesion and communication, as well as the adverse effects of uncertainty. Within this context, this paper introduces an event-based adaptive flocking control law for USVS to address these issues. Firstly, an integrated dual-mode potential function, combining a novel artificial potential function (APF) and a directionally consistent potential function (DCPF), is designed to enhance flocking cohesion while guaranteeing connectivity. Then, a boundary-locked event-triggered (BLET) mechanism effectively reduces the communication load with computable minimum inter-event time (MIET) and maximum triggering interval time (MTIT). Finally, a reinforcement learning-based echo state network (RLESN) is incorporated to compensate for unmodeled dynamics and external disturbances, thereby significantly improving the system’s robustness. Simulation results and comparative analyses validate the effectiveness and advantages of the proposed methodology.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 29-40"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Motion-vibration hybrid control of flexible-base-joint-link space manipulation system capturing target spacecraft using barrier Lyapunov function 基于barrier Lyapunov函数的柔基-关节-连杆空间操纵系统运动-振动混合控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.09.040

Xiaodong Fu, Zhaokui Wang

This study analyses the space manipulation system's contact collision dynamics of capturing a target spacecraft, considering the influence of multiple vibrations in the base, joints, and links. The dynamic models of a flexible-base-joint-link space manipulation system and the target spacecraft are derived. The impact generated by the capture collision is examined. A dynamic model for the combined spacecraft system is established. Using singular perturbation theory, the model is decomposed into controllable subsystems. A motion-vibration hybrid controller is proposed, which incorporates an adaptive constrained neural network control based on the barrier Lyapunov function, hybrid trajectory method, and linear quadratic optimal control. The controller satisfies the torque-limited requirements, and its parameters are adaptively updated. Numerical examples are presented to substantiate the validity of the main results.

考虑基座、关节和连杆多重振动的影响，对空间操纵系统捕获目标航天器的接触碰撞动力学进行了分析。建立了柔基-关节-连杆空间操纵系统和目标航天器的动力学模型。检查捕获碰撞产生的影响。建立了组合航天器系统的动力学模型。利用奇异摄动理论，将模型分解为多个可控子系统。提出了一种运动-振动混合控制器，该控制器结合了基于barrier Lyapunov函数的自适应约束神经网络控制、混合轨迹法和线性二次最优控制。该控制器满足力矩限制要求，参数自适应更新。通过数值算例验证了主要结果的有效性。

引用次数: 0

Adaptive time-frequency signal enhancement and deep spatial-temporal fusion for noise-resistant bearing fault diagnosis 基于自适应时频信号增强和深度时空融合的抗噪声轴承故障诊断。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.019

Xin Li , Bingyin Wang , Jin Lv , Lixin Wei , Kai Ma

In industrial environments, substantial background noise often obscures the crucial impact and periodic features within bearing vibration signals, hindering the efficacy of conventional diagnostic methods. To address this challenge, this paper proposes a novel fault diagnosis framework for rolling bearings, initiated by an advanced signal enhancement stage using a time–frequency extension of adaptive filtering (TFEAF) method. This method effectively enhances the signal’s time–frequency representation, achieving robust denoising and revealing the underlying fault characteristics previously masked by noise. Subsequently, we introduce a novel Huge Kernel Convolutional Bidirectional Long Short-Term Memory Network with a Cross-Attention mechanism (HCBM-CANet). This network is specifically designed to extract deep spatial and temporal features from the denoised signal. The integrated cross-attention mechanism synergistically fuses these features, achieving significant boosts in diagnostic precision under complex operating conditions. Experimental results on the CWRU and Paderborn University datasets demonstrate the superiority of our approach. Under high-noise scenarios, the proposed TFEAF-HCBM-CANet framework achieves an average diagnostic accuracy exceeding 99 %, outperforming seven state-of-the-art network models. These findings validate the exceptional robustness and effectiveness of our method for processing signals heavily corrupted by noise.

在工业环境中，大量的背景噪声往往掩盖了轴承振动信号中的关键影响和周期性特征，阻碍了传统诊断方法的有效性。为了解决这一挑战，本文提出了一种新的滚动轴承故障诊断框架，该框架由使用时频扩展自适应滤波（TFEAF）方法的高级信号增强阶段启动。该方法有效地增强了信号的时频表征，实现了鲁棒去噪，揭示了之前被噪声掩盖的潜在故障特征。随后，我们介绍了一种新的具有交叉注意机制的巨大核卷积双向长短期记忆网络（HCBM-CANet）。该网络专门用于从去噪信号中提取深层时空特征。集成的交叉注意机制协同融合了这些特征，在复杂的操作条件下显著提高了诊断精度。在CWRU和帕德伯恩大学数据集上的实验结果证明了我们方法的优越性。在高噪声情况下，提出的TFEAF-HCBM-CANet框架的平均诊断准确率超过99%，优于7个最先进的网络模型。这些发现验证了我们的方法在处理严重受噪声干扰的信号时的出色鲁棒性和有效性。

{"title":"Adaptive time-frequency signal enhancement and deep spatial-temporal fusion for noise-resistant bearing fault diagnosis","authors":"Xin Li , Bingyin Wang , Jin Lv , Lixin Wei , Kai Ma","doi":"10.1016/j.isatra.2025.11.019","DOIUrl":"10.1016/j.isatra.2025.11.019","url":null,"abstract":"<div><div>In industrial environments, substantial background noise often obscures the crucial impact and periodic features within bearing vibration signals, hindering the efficacy of conventional diagnostic methods. To address this challenge, this paper proposes a novel fault diagnosis framework for rolling bearings, initiated by an advanced signal enhancement stage using a time–frequency extension of adaptive filtering (TFEAF) method. This method effectively enhances the signal’s time–frequency representation, achieving robust denoising and revealing the underlying fault characteristics previously masked by noise. Subsequently, we introduce a novel Huge Kernel Convolutional Bidirectional Long Short-Term Memory Network with a Cross-Attention mechanism (HCBM-CANet). This network is specifically designed to extract deep spatial and temporal features from the denoised signal. The integrated cross-attention mechanism synergistically fuses these features, achieving significant boosts in diagnostic precision under complex operating conditions. Experimental results on the CWRU and Paderborn University datasets demonstrate the superiority of our approach. Under high-noise scenarios, the proposed TFEAF-HCBM-CANet framework achieves an average diagnostic accuracy exceeding 99 %, outperforming seven state-of-the-art network models. These findings validate the exceptional robustness and effectiveness of our method for processing signals heavily corrupted by noise.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 284-304"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145566654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Funnel control based on unknown system dynamics estimator for hydraulically-driven lower limb exoskeleton robot 基于未知系统动力学估计的液压驱动下肢外骨骼机器人漏斗控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.012

Jinsong Zhao , Huidong Hou , Yunpeng Zhang , Quan Miao

The hydraulically-driven lower limb exoskeleton robot (HDLLER) can enhance the motion capabilities of human lower limbs. However, due to inherent uncertainties and external human–robot coupling disturbances, it poses significant challenges to precise trajectory tracking control. Therefore, a novel funnel control (FC) strategy based on an unknown system dynamics estimator (USDE) is proposed to compensate for unknown internal and external dynamic influences, thus further improving robot performance. Firstly, the HDLLER high-order dynamic model containing human–robot coupling disturbances is transformed into a Brunovsky canonical form, effectively circumventing the ‘explosion of complexity’ problem in high order strict feedback systems. Subsequently, a set of high gain observers (HGO) is introduced to reconstruct the states of the transformed system. A modified funnel function is embedded in feedback controller to constrain the tracking error within prescribed boundaries, ensuring satisfactory transient and steady-state performances. Additionally, a simple yet effective USDE is incorporated to compensate for the lumped unknown dynamics. Different comparative simulations and gait experiments have verified the effectiveness of the proposed control method.

液压驱动的下肢外骨骼机器人（HDLLER）可以增强人体下肢的运动能力。然而，由于固有的不确定性和外部人-机器人耦合干扰，对精确的轨迹跟踪控制提出了重大挑战。为此，提出了一种基于未知系统动力学估计器（USDE）的漏斗控制策略，补偿未知的内外动态影响，从而进一步提高机器人的性能。首先，将包含人机耦合扰动的HDLLER高阶动态模型转化为布鲁诺夫斯基规范形式，有效地规避了高阶严格反馈系统中的“复杂性爆炸”问题。随后，引入一组高增益观测器（HGO）来重建变换后的系统状态。在反馈控制器中嵌入一个改进的漏斗函数，将跟踪误差限制在规定的范围内，保证了满意的瞬态和稳态性能。此外，一个简单而有效的USDE被纳入补偿集总未知动态。不同的对比仿真和步态实验验证了所提控制方法的有效性。

{"title":"Funnel control based on unknown system dynamics estimator for hydraulically-driven lower limb exoskeleton robot","authors":"Jinsong Zhao , Huidong Hou , Yunpeng Zhang , Quan Miao","doi":"10.1016/j.isatra.2025.11.012","DOIUrl":"10.1016/j.isatra.2025.11.012","url":null,"abstract":"<div><div>The hydraulically-driven lower limb exoskeleton robot (HDLLER) can enhance the motion capabilities of human lower limbs. However, due to inherent uncertainties and external human–robot coupling disturbances, it poses significant challenges to precise trajectory tracking control. Therefore, a novel funnel control (FC) strategy based on an unknown system dynamics estimator (USDE) is proposed to compensate for unknown internal and external dynamic influences, thus further improving robot performance. Firstly, the HDLLER high-order dynamic model containing human–robot coupling disturbances is transformed into a Brunovsky canonical form, effectively circumventing the ‘explosion of complexity’ problem in high order strict feedback systems. Subsequently, a set of high gain observers (HGO) is introduced to reconstruct the states of the transformed system. A modified funnel function is embedded in feedback controller to constrain the tracking error within prescribed boundaries, ensuring satisfactory transient and steady-state performances. Additionally, a simple yet effective USDE is incorporated to compensate for the lumped unknown dynamics. Different comparative simulations and gait experiments have verified the effectiveness of the proposed control method.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 455-464"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145558498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Compensation function observer based model-free adaptive boundary layer sliding mode control for hydraulic manipulators with dead-zone compensation 基于补偿函数观测器的无模型自适应边界层滑模控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.008

Minxuan Zha, Haoping Wang, Yang Tian

In this paper, a compensation function observer based model-free adaptive boundary layer sliding mode control (CFO-DIBLSMC) is proposed for hydraulic manipulators with dead-zone compensation. The proposed CFO-DIBLSMC adopts a dual-loop structure, comprising a force sub-control loop for precise force tracking using an adaptive admittance controller and a position sub-control loop where the complex hydraulic manipulator dynamics are approximated by an ultra-local model (ULM) to establish a model-free control framework. Then, considering the unknown dead-zone in the directional valve, a smooth dead-zone inverse method with online parameter adaptation is employed to compensate for dead-zone uncertainties. Besides, a compensation function observer is designed based on ULM to estimate lumped uncertainties of the system, achieving zero error estimation and robustness against high-frequency disturbances. Moreover, a nonsingular fast terminal sliding mode (NFTSM) sub-control law is constructed to accelerate error convergence, incorporating an adaptive switching sliding gain law within a boundary layer framework. The effectiveness of CFO-DIBLSMC is verified through comparative co-simulations against conventional control methods under dead-zone and joint friction disturbances.

针对具有死区补偿的液压机械臂，提出了一种基于补偿函数观测器的无模型自适应边界层滑模控制（CFO-DIBLSMC）。所提出的CFO-DIBLSMC采用双环结构，包括利用自适应导纳控制器进行精确力跟踪的力子控制环和利用超局部模型（ULM）逼近复杂液压机械臂动力学的位置子控制环，建立无模型控制框架。然后，考虑换向阀存在未知死区，采用在线参数自适应的光滑死区逆方法补偿死区不确定性；此外，基于ULM设计了补偿函数观测器来估计系统的集总不确定性，实现了零误差估计和对高频干扰的鲁棒性。此外，构造了非奇异快速终端滑模子控制律来加速误差收敛，在边界层框架内引入了自适应切换滑动增益律。通过与传统控制方法在死区干扰和关节摩擦干扰下的对比联合仿真，验证了CFO-DIBLSMC的有效性。

{"title":"Compensation function observer based model-free adaptive boundary layer sliding mode control for hydraulic manipulators with dead-zone compensation","authors":"Minxuan Zha, Haoping Wang, Yang Tian","doi":"10.1016/j.isatra.2025.11.008","DOIUrl":"10.1016/j.isatra.2025.11.008","url":null,"abstract":"<div><div>In this paper, a compensation function observer based model-free adaptive boundary layer sliding mode control (CFO-DIBLSMC) is proposed for hydraulic manipulators with dead-zone compensation. The proposed CFO-DIBLSMC adopts a dual-loop structure, comprising a force sub-control loop for precise force tracking using an adaptive admittance controller and a position sub-control loop where the complex hydraulic manipulator dynamics are approximated by an ultra-local model (ULM) to establish a model-free control framework. Then, considering the unknown dead-zone in the directional valve, a smooth dead-zone inverse method with online parameter adaptation is employed to compensate for dead-zone uncertainties. Besides, a compensation function observer is designed based on ULM to estimate lumped uncertainties of the system, achieving zero error estimation and robustness against high-frequency disturbances. Moreover, a nonsingular fast terminal sliding mode (NFTSM) sub-control law is constructed to accelerate error convergence, incorporating an adaptive switching sliding gain law within a boundary layer framework. The effectiveness of CFO-DIBLSMC is verified through comparative co-simulations against conventional control methods under dead-zone and joint friction disturbances.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"168 ","pages":"Pages 211-224"},"PeriodicalIF":6.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145643920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

ISA transactions

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀