ISA transactions最新文献

{"title":"Singular-perturbation-based sliding mode control with practical slackness prevention for elastic antagonistic cable-driven joints.","authors":"Zhiyi Tu, Xudong Zheng, Jiangbo Zhao, Yang Deng, Bin Liang, Junzheng Wang","doi":"10.1016/j.isatra.2026.09.036","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.036","url":null,"abstract":"<p><p>This paper investigates robust tracking and practical slackness prevention for elastic antagonistic cable-driven joints. A representative elbow joint of a 7-DOF cable-driven manipulator (CDM) is considered because it has a typical motor, cable and joint coupling structure. A coupled dynamic model is established by considering cable elasticity, motor dynamics, joint motion, and the positive cable tension condition. Based on singular perturbation theory, the dynamics are separated into slow joint motion and fast cable tension dynamics. For the slow dynamics, sliding mode control with a tangent barrier gain within the singular perturbation framework (SP-tanBGSMC) is developed to improve tracking robustness and constrain the sliding variable. For the fast dynamics, a fast loop deformation regulator is introduced to restrict cable deformation and support positive cable tension within a prescribed margin. The analysis yields ultimate bounds for the slow loop variables and practical boundedness of the overall closed loop system. Simulations and representative experiments support robust tracking and practical preservation of the cable deformation constraint under the tested conditions; the experiments provide positive model-based tension estimates, while the simulation with a displacement disturbance on the motor side supports practical slackness prevention.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-constrained data-driven prediction and multi-objective optimization of road noise in electric vehicles.","authors":"Mingliang Yang, Yingqi Yin, Jian Pang, Likang Fan, Weiping Ding, Haibo Huang","doi":"10.1016/j.isatra.2026.09.042","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.042","url":null,"abstract":"<p><p>The overall interior noise level of pure electric vehicles is relatively low, making road noise a dominant factor affecting in-cabin ride quality. Mid- and low-frequency structure-borne road noise mainly arises from the coupled vibration of the tire-suspension system and exhibits multiple spectral peaks, strong nonlinearity, and high sensitivity to structural parameters, posing challenges for accurate prediction and optimization. Conventional experimental and simulation-based methods are applicable to road noise analysis but often involve complex modeling procedures and limited efficiency. To address these limitations, innovations are introduced in both model architecture and physical consistency. First, a road-noise prediction model based on a multi-head attention mechanism is proposed. Key structural parameters, including tire properties, suspension bushings, and dampers, are used as inputs, while the multi-head attention structure enhances feature extraction and weight allocation across different frequency bands, thereby improving the representation accuracy and generalization capability for multi-peak and nonlinear road noise. Second, a physics-constrained learning framework is established by embedding amplitude-frequency response constraints into the loss function, ensuring that the learning process follows vibro-acoustic transmission laws. This strategy reduces prediction bias at typical peak frequencies and improves model interpretability. Based on these strategies, a physics-constrained multi-head attention long short-term memory model is constructed and integrated with NSGA-III to achieve multi-objective collaborative optimization of road noise. Full-vehicle road tests are conducted for validation.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149171578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A wavelet elastic metric network for limited-data mechanical fault diagnosis of transformer on-load tap changers.","authors":"Zhixin Chen, Tong Zhao, Runze Qi, Bohao Peng, Tianyu Duan, Xiaolong Wang","doi":"10.1016/j.isatra.2026.09.039","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.039","url":null,"abstract":"<p><p>Reliable fault diagnosis of on-load tap changers (OLTCs), a critical component for transformer voltage regulation, is essential for ensuring the safe operation of power systems. However, the nonstationary characteristics of switching vibration signals and limited fault data restrict the effectiveness of conventional diagnostic methods. To address this issue, a Wavelet Elastic Metric Network (WEMNet) is proposed. A Wavelet-enhanced Multiscale Feature Encoder is designed to extract transient impacts and multiscale time-frequency features from vibration signals, while an elastic metric mechanism adaptively adjusts feature distances according to fault-related variations, improving discriminability under limited-data conditions. Experimental results under typical OLTC mechanical fault conditions demonstrate that the proposed method achieves stable diagnostic performance in few-shot scenarios, providing an effective solution for condition monitoring of OLTC.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional-Order Super-Twisting Sliding Mode MPPT Control with Fixed-Time Convergence for Photovoltaic Systems under Partial Shading Conditions.","authors":"Jianxiang Yang, Yiran Fan, Zekai Ying, Jianbin Xiong, Qi Wang","doi":"10.1016/j.isatra.2026.09.027","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.027","url":null,"abstract":"<p><p>The power-voltage characteristics of photovoltaic systems become nonconvex under partial shading conditions, leading to significant efficiency degradation due to varying solar irradiance and temperature. To address this challenge, an improved finite-time fractional-order super-twisting fast terminal sliding mode control strategy is proposed in this work, achieving fixed-time convergence to the global maximum power point independent of initial conditions. By integrating Caputo fractional calculus with a super-twisting reaching law, the proposed method effectively suppresses chattering while ensuring finite-time stability, with convergence time analytically bounded via Lyapunov theory.Under uniform irradiation, the proposed controller demonstrates significantly improved tracking efficiency compared to conventional methods. In partial shading scenarios, high tracking accuracy and a remarkably fast settling time are attained, confirming the controller's high precision, rapid dynamic response, and strong robustness against environmental uncertainties. The findings indicate that the proposed strategy is a highly effective solution for real-world PV systems under both uniform and partial shading conditions.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-source imbalanced generalization wavelet network for heterogeneous imbalanced mechanical fault diagnosis under unknown time-varying working conditions.","authors":"Yefeng Li, Hong Jiang, Xiangfeng Zhang, Dong Han","doi":"10.1016/j.isatra.2026.09.033","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.033","url":null,"abstract":"<p><p>In recent years, fault diagnosis of rotating machinery under unknown working conditions has been investigated. However, in real industrial scenarios, due to the complexity of equipment and the diversity of operating conditions, problems such as class imbalance and domain shift frequently occur under unknown working conditions. In addition, there are interferences from non-stationary time-varying rotational speed conditions and insufficient revelation of fault characteristics, which severely limit the cross-domain generalization performance of models. Therefore, this paper proposes a Multi-Source Imbalanced Generalization Wavelet Network (MS-IGWN). Firstly, a wavelet-enhanced residual network is constructed as the feature extractor. A db4-initialized learnable wavelet filter bank is embedded in the residual network to obtain complementary frequency-selective representations and learn multi-scale discriminative features, and the residual network is combined to learn deep discriminative features. Then, Multi-Head Self-Attention (MHSA) and Multi-order Gated Aggregation Block (MogaBlock) are introduced to strengthen the spatiotemporal correlation of features and the focusing of key information. Secondly, a Semantic-Consistent Mixup (SCMix) mechanism is introduced to enrich minority-class representations by interpolating same-label samples from different source domains. In addition, Cross-Domain Invariant Triplet Loss (CITL) promotes cross-domain intra-class compactness and inter-class separation. Performance tests of MS-IGWN are conducted on the University of Ottawa (Ottawa) bearing dataset and the Mechanical Diagnosis Gear dataset (LJS). Imbalanced domain generalization experiments under unknown time-varying rotational speed conditions show that the proposed MS-IGWN method has better clustering performance, higher classification accuracy, as well as superior generalization and robustness.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive sub-Nyquist sampling and its application in rotating machinery fault detection.","authors":"Yanqing Zhao, Wei Jiang, Kondo H Adjallah, Alexandre Sava","doi":"10.1016/j.isatra.2026.09.032","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.032","url":null,"abstract":"<p><p>In rotating machinery fault detection, oversampling induces three forms of data redundancy: (1) redundancy resulting from conventional Nyquist-based sampling, (2) redundancy induced by changes in the degradation state of the rotating machinery's components, and (3) redundancy caused by operating over a wide range of rotational speeds. To resolve these data redundancies, this paper proposes a novel adaptive sub-Nyquist sampling (ASNS) technique. ASNS precisely aligns the sampling strategy with the shaft's rotational period and dynamically adjusts the number of samples per rotational period based on condition awareness. We applied ASNS to fault detection and proposed an ASNS-based method for detecting faults in rotating machinery. The ASNS-based fault detection method does not require signal reconstruction; instead, it analyzes the ASNS data to extract fault features. The effectiveness of the ASNS-based fault detection method is validated using simulated and experimental data. The results demonstrate that the ASNS-based fault detection method improves data acquisition performance and significantly reduces the sampling frequency while maintaining detection reliability and accuracy. This advantage effectively reduces the costs of data acquisition, transmission, storage, and processing, thereby optimizing predictive maintenance decisions. Additionally, the ASNS-based fault detection method has low computational complexity and supports real-time fault detection.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Path planning, obstacle avoidance, and trajectory control of a differential-drive mobile robot based on improved RRT^∗-APF and nonsingular quasi-sliding mode techniques.","authors":"Jinping Ye, Chen Wang, Wuyi Luo, Xianhua Li, Tao Chao, Jiyu Zhang, Gang Shen, Qing Guo","doi":"10.1016/j.isatra.2026.09.037","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.037","url":null,"abstract":"<p><p>This study presents a framework for path planning, trajectory generation, and trajectory control of a differential-drive mobile robot in obstacle-populated environments. In the path-planning phase, an improved RRT^∗-APF (rapidly-exploring random tree star and artificial potential field) method is developed by integrating RRT^∗ with APF, safety inflation, and a steering-aware smoothness cost. Furthermore, parent-node selection and connection in RRT^∗ are determined by a indicator designed to consider path length, obstacle risk, and smoothness. The generated path is optimized by greedy pruning and cubic B-spline smoothing to obtain a trackable geometric route. In addition, a phase-plane time-optimal method is used to transform the smoothed path into a feasible time-indexed trajectory under velocity and acceleration constraints. In the trajectory-control phase, a tracking module based on nonsingular quasi-sliding mode control (NSQSMC) is implemented as a practical component to execute the generated time-indexed trajectory on the physical robot platform. The simulation and experimental results verify the effectiveness of the proposed framework. Compared with the structurally closest RRT^∗-APF baseline, the proposed planner reduces composite path cost by 5.9% and 2.9% and obstacle-risk cost by 32.5% and 12.6% in the mixed-obstacle and maze scenarios, respectively. These improvements remain statistically significant after Holm correction. The greedy-pruning-B-spline pipeline further improves trajectory smoothness by reducing accumulated heading variation by 22.22% and 17.34% in the two scenarios while maintaining sufficient obstacle clearance. Moreover, compared with the conventional sliding mode controller (SMC), the NSQSMC-based tracking implementation reduces the planar position-error IAE, MAE, and RMSE by 73.2%, 72.3%, and 67.3%, respectively. Compared with the backstepping controller (BC), the corresponding reductions are 56.2%, 55.2%, and 46.7%, respectively.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model predictive displacement controller with an adaptive ESO and fuzzy dead-zone compensator of drill-arm for a hydraulic roofbolter.","authors":"Yinan Guo, Feng Jiao, Zhen Zhang, Guowei Zhu, Peiyao Ji, Jing Liang, Shirong Ge","doi":"10.1016/j.isatra.2026.09.034","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.034","url":null,"abstract":"<p><p>A hydraulic roof bolter is the key piece of equipment for installing anchor bolts in roadways, and its position regulated by the drill-arm directly determines the support quality. Due to the complex drilling environment with unknown internal and external disturbances, as well as inherent dead zone of the proportional directional valve, anti-disturbance ability and tracking accuracy were limited. To address these challenges, the drill-arm displacement system is first formulated by considering nonlinear friction. Then, a variable-domain fuzzy dead-zone compensator is designed to eliminate the negative effect of dead-zone in the proportional directional valve. An ANLESO is further developed to enhance the disturbance rejection capability. By integrating the above two, an augmented feedback linearization model predictive controller is presented to improve the displacement tracking accuracy of the drill-arm. Experimental results conducted on a test platform of drill-arm for a hydraulic roofbolter validated the effectiveness and superiority of the proposed method.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model-based extended state observer for discrete-time linear multivariable systems.","authors":"Jinfeng Chen, Zhiqiang Gao, Qin Lin","doi":"10.1016/j.isatra.2026.09.035","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.035","url":null,"abstract":"<p><p>In the absence of a detailed and accurate plant model, the extended state observer (ESO) has been clearly shown to be an effective tool in both control applications and theoretical analysis. Less clear is how to further enhance such a tool when the model is available, however inaccurate, together with additional measurement information. To this end, a model-based ESO (MB-ESO) and its generalized form (GMB-ESO) for discrete-time linear multivariable systems are developed in this paper by explicitly incorporating the additional state-space model and measurement information, which is otherwise bypassed by the conventional ESO. In addition, the GMB-ESO is shown to accommodate systems with non-diagonal disturbance gain matrices. Necessary and sufficient conditions for the existence of the MB-ESO and GMB-ESO are established in terms of a well-defined disturbance vector relative degree and the absence of invariant zeros in the disturbance-to-measurement path. Under noise-free measurements and infinite observer bandwidth, exact disturbance reconstruction can be achieved within a finite number of steps, while under measurement noise, ε-accurate reconstruction can be guaranteed with finite observer bandwidth. Finally, the disturbance reconstruction error of the MB-ESO is shown, in both theoretical analysis and simulation, to decrease monotonically with time when the disturbance gain matrix is diagonal, and an explicit bound on the disturbance estimation error is derived.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergy-driven time-frequency adversarial network for characterizing fault characteristic frequencies in rotating machinery.","authors":"Haoran Zhao, Dezun Zhao, Tianyang Wang, Lingli Cui","doi":"10.1016/j.isatra.2026.09.028","DOIUrl":"https://doi.org/10.1016/j.isatra.2026.09.028","url":null,"abstract":"<p><p>Rotating machinery often operates under variable-speed conditions, which generate non-stationary signals containing dense and crossing instantaneous frequencies (IFs), posing significant challenges to existing time-frequency analysis (TFA). Accordingly, the synergy-driven time-frequency adversarial network (SDTFAN) is proposed. First, a learnable time-frequency characterizing module (LTFCM) is designed, where the frequency and chirp-rate of the Chirplet kernel are adaptively learned to optimize the time-frequency mapping process and generate standardized multi-channel time-frequency representations (TFRs). Second, a synergistic time-frequency enhancement framework (STFEF) is constructed with the proposed time-frequency distillation attention module (TFDAM) and time-frequency axial enhancement module (TFAEM). These modules refine local time-frequency features, suppress background interference and enhance global structural dependencies to improve the TFR energy concentration. Finally, a semi-supervised adversarial training strategy is proposed to alleviate the dependence on paired time-frequency labels, namely the ideal TFR and penalty TFR, during model training by introducing adversarial constraints from the unlabeled branch to exploit potential time-frequency features. The results obtained from both simulated signals and planetary gearbox and bearing data demonstrate that the SDTFAN can effectively represent dense and crossing IFs. The Rényi entropy further confirms that the SDTFAN achieves better energy concentration than several TFA methods.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}