ISA transactions最新文献

{"title":"Ridge-based general synchrosqueezing transform for flexible thin-wall bearing fault diagnosis.","authors":"Yanjiang Yu, Xuezhi Zhao","doi":"10.1016/j.isatra.2025.08.040","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.040","url":null,"abstract":"<p><p>Accurate fault diagnosis in flexible thin-wall bearings is crucial for harmonic drive reliability but remains challenging, as fault impulses are often masked by strong operational vibrations. In response to this challenge, a ridge-based general synchrosqueezing transform (RGST) is proposed in this paper. This method unifies time-frequency analysis by operating at the ridge level, using energy trajectories extracted from both instantaneous frequency and group delay estimators. Key features of RGST include a binary ridge expansion mask to enhance energy concentration and suppress noise, and an agglomerative clustering algorithm to separate signal components. Experimental results demonstrate that RGST achieves a concentrated time-frequency representation with superior component separation and noise robustness, thereby improving the reliability of fault diagnosis under multiple fault conditions in flexible thin-wall bearings.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144983546","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":"Aerodynamic parameter identification method based on physics-informed radial basis function-deep neural networks.","authors":"Jungu Chen, Junhui Liu, Jiayuan Shan, Jianan Wang","doi":"10.1016/j.isatra.2025.08.039","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.039","url":null,"abstract":"<p><p>This paper investigates the perturbations estimation between the real and nominal aerodynamic parameters. To address this issue, this study proposes an aerodynamic parameter identification method based on the physics-informed radial basis function-deep neural network (PIRBF-DNN). PIRBF-DNN utilizes an integration-based loss function to achieve precise estimation of aerodynamic parameters perturbations and adopts a radial basis function-deep neural network (RBF-DNN) structure to enhance fitting capability of the network. The proposed identification method is validated through simulation in different scenarios and comparison with other aerodynamic parameters identification methods based on physics-informed neural networks (PINNs).</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984057","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":"Prescribed-time control weak disturbance decoupling problems for strict-feedback-like systems with unknown control coefficients, disturbances and zero dynamics.","authors":"Na Wang, Xiaoping Liu, Yajing Zhao, Xinpeng Guo, Cungen Liu, Huanqing Wang","doi":"10.1016/j.isatra.2025.08.026","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.026","url":null,"abstract":"<p><p>In many applications, such as manipulators for an assembly line, a prescribed-time controller is required to complete a task at prescribed-time and to continue operating for long time. However, the existing prescribed-time controllers are not well designed for long time operation because prescribed-time adjustment functions used in controllers are not well-defined in some publications and are not differentiable in others. In addition, disturbance decoupling has not been addressed for prescribed-time control. Therefore, the main objective of the paper is to design an adaptive controller so that the impact of disturbances is attenuated for scenarios with disturbances, while at the same time, the system output error is bounded at prescribed-time by positive constant which can be made arbitrarily small and the bounded stability of states can be ensured for situations without disturbances. To this end, the existing prescribed-time adjustment functions are smoothed by using linear combination of exponential functions so that they are sufficiently differentiable for infinite-time, a new weighted norm is defined, and an adaptive prescribed-time almost disturbance decoupling controller is constructed for uncertain strict-feedback-like nonlinear systems with zero dynamics, disturbances and unknown virtual control coefficients. Unboundedness of high-order derivatives of virtual and actual control signals caused by nondifferentiability of the existing prescribed-time adjustment functions is overcome by the proposed sufficiently differentiable prescribed-time adjustment function. Comparative simulation results show that the proposed controller performs better than the existing controllers before and after prescribed-time and is effective for disturbance attenuation.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144983510","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":"Event-triggered optimal control for modular reconfigurable manipulators with input constraints based on model predictive control.","authors":"Fan Zhou, Yifan Zhang, Tianhao Ma","doi":"10.1016/j.isatra.2025.08.041","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.041","url":null,"abstract":"<p><p>This paper proposes an event-triggered optimal control method for modular reconfigurable manipulators(MRMs) based on model predictive control(MPC). By using a decentralized optimization method based on MPC, the optimal control problem of MRMs is transformed into independent optimization tasks for each module, while a global MPC optimization framework is utilized to coordinate the modules, ultimately optimizing the overall performance of the entire system. In order to avoid the safety hazards caused by excessive torque, hyperbolic tangent function is added to constrain the input torque. Considering the inaccuracies in the modeling process, adaptive dynamic programming (ADP) is introduced into MPC to improve the robustness of the system. A critical neural network (NN) is designed to solve the Hamilton-Jacobi-Bellman (HJB) equation, yielding the system's optimal solution. Lyapunov theory is used to prove that the trajectory tracking error is uniformly ultimately bounded (UUB). Finally, the comparative experimental results demonstrate that the proposed method achieves significant improvements in reducing tracking error, minimizing resource consumption, and enhancing constrained torque capability.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002256","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":"Improved fast non-singular adaptive super-twisting sliding mode control based on radial basis function neural network approximation for robot joint module.","authors":"Xiao Lin, Junyang Li, Yankui Song, Chengguo Liu, Tianyou Yang","doi":"10.1016/j.isatra.2025.08.037","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.037","url":null,"abstract":"<p><p>This study proposes an improved fast non-singular adaptive super-twisting control scheme based on neural network to address the precise control issues of robot joint modules. Firstly, to facilitate the application of advanced control algorithms, a second-order state-space model of the joint module considering nonlinear friction and stiffness is established using the Lagrangian energy equation method. Then, an improved fast non-singular terminal sliding surface is proposed to avoid singularity and accelerate convergence. Subsequently, an equivalent control law compensator using a radial basis function neural network is designed to counteract the impact of uncertain model factors, thereby ensuring the system states closely follow the sliding surface. Furthermore, an adaptive switching control law is designed that does not require precise disturbance information, enhancing its practicality for engineering applications. Finally, simulation and experimental results under two different reference trajectories and in the presence of external disturbances demonstrate the superior trajectory tracking capability and disturbance rejection performance of the proposed control scheme.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984147","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":"Disturbance rejection event-triggered robust nonlinear model predictive control for underactuated unmanned surface vehicle against DoS attacks without velocity measurements.","authors":"Na Feng, Defeng Wu, Hongliang Yu, Zheng You, Wanli Tu","doi":"10.1016/j.isatra.2025.08.031","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.031","url":null,"abstract":"<p><p>This paper presents a disturbance rejection event-triggered nonlinear model predictive control (DR-ETNMPC) method for underactuated unmanned surface vehicle (USV) subject to denial-of-service (DoS) attacks and lacking velocity measurements. A nonlinear extended state observer (NESO) is employed to estimate both unknown velocities and lumped disturbances, while a disturbance rejection nonlinear model predictive controller (DRNMPC) is designed to enforce actuator saturation constraints. To reduce computational load of the DRNMPC, an event-triggered mechanism is introduced, and a DoS attack defense mechanism is introduced to guarantee that the USV maintains high-precision tracking performance under DoS attacks. Rigorous analysis is conducted to ensure recursive feasibility and closed-loop stability. Simulation results verify the method's effectiveness and superiority, demonstrating notable improvements in both control precision and computational efficiency.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984135","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":"Cooperative game robust coordination control for distributed electric vehicle under sharply turning roads.","authors":"Wei Li, Chunyan Wang, Wanzhong Zhao, Linfeng Lv, Jiabing Gao","doi":"10.1016/j.isatra.2025.08.032","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.032","url":null,"abstract":"<p><p>As key technologies for distributed electric vehicle (DEV), four-wheel steering (4WS) and four-wheel independent drive (4WID) can effectively enhance the path-tracking accuracy and lateral stability. However, when under a sharply turning road, tire nonlinearity and longitudinal-lateral coupling effects are significantly exacerbated, leading to increased complexity in dynamic modeling. Meanwhile, control objective conflicts between 4WS and 4WID, as well as disturbances including time-varying speed, may reduce lateral stability during precise path-tracking. To address these challenges, we propose a cooperative game robust coordination controller (CGRCC) based on Takagi-Sugeno (T-S) fuzzy. First, a vehicle-road discrete error model considering tire nonlinearity and longitudinal-lateral coupling effects is established based on T-S fuzzy, which precisely captures the dynamic characteristics of individual tires and enhances DEV modeling accuracy. Second, a cooperative game coordination controller is designed based on the dynamic interaction between 4WS and 4WID, achieving multi-actuator collaborative optimization to harmonize the objective coupling conflicts between precise path-tracking and lateral stability. Finally, a fuzzy Lyapunov-based H_∞ disturbance suppressor is developed to mitigate the impact of the disturbances, including time-varying vehicle speed, on system performance. The experimental results show that under large curvature double line changes, CGRCC reduces the path-tracking error by 33.3 %, 48.1 % and 60.3 %, and the lateral speed error by 15.5 %, 16.3 % and 24.6 %, respectively, compared with the comparison controllers, demonstrating the efficacy and preeminence of CGRCC under sharply turning roads.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984163","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":"Approximation-free finite-time control for uncertain active suspensions with unknown time-varying input delays.","authors":"Wenbo Wang, Shuang Liu, Dingxuan Zhao, Cong Zhang","doi":"10.1016/j.isatra.2025.08.024","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.024","url":null,"abstract":"<p><p>This article investigates a new approximation-free finite-time control method for active suspension systems (ASSs) to address uncertain nonlinearities and unknown time-varying input delays (UTIDs), while enhancing suspension performance. First, to improve the transient performance of ASSs, a unique finite-time prescribed performance function (FPPF) is designed to ensure that the suspension motion converges to a predetermined range within a finite time. Then, a novel compensator is developed to resolve the impact of unknown input delays in the closed-loop system. Finally, an approximation-free finite-time control method is presented for uncertain ASSs using the FPPF and the compensator. In this method, neural networks and fuzzy logic systems are not required to handle system uncertainties, and finite-time prescribed performance convergence of suspension motion can be achieved even in the presence of UTIDs. To exhibit the usefulness of the proposed method, a combined dynamic simulator is built using MATLAB and Simpack, a professional vehicle simulation software. Simulation results are presented to validate the effectiveness of the proposed method and show improved suspension performance.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984183","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":"Fault identification for rolling bearing based on ITD-ILBP-Hankel matrix.","authors":"Mingyue Yu, Ziru Ma, Yingdong Gao, Xiangdong Ge, Yunbo Wang","doi":"10.1016/j.isatra.2025.08.029","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.029","url":null,"abstract":"<p><p>When a failure occurs in bearings, vibration signals are characterized by strong non-stationarity and nonlinearity. Therefore, it is difficult to sufficiently dig fault features. 1D local binary pattern (1D-LBP) has the advantageous feature to effectively extract local information of signals. Unexpectedly, it is vulnerable to the influence of noise when directly applied which led to quantization is inaccurate. To improve the accuracy of bearing fault diagnosis and solve the problem of imprecise quantization, the paper has studied the quantization criterion of 1D-LBP and proposed a combined method of improved 1D-LBP and intrinsic time-scale decomposition (ITD) and Hankel matrix (ITD-ILBP-Hankel). Firstly, a new signal pretreating strategy is proposed to further highlight feature information of bearing failure. Original signals are subjected to first-order difference operation to further highlight the impact feature of bearing failure and differential signals (non-original signals) are decomposed by ITD to obtain proper rotation components (PRCs). Secondly, to correctly quantize signals, a new quantization criterion is applied to 1D-LBP. Classical 1D-LBP is likely to be affected by individual extreme values or strong noise when quantizing signals inside window with median are threshold; meanwhile the root mean square (RMS) of signals can reflect the distribution of energy and represent the impact feature of signals in bearing fault. Therefore, RMS of signals is taken as threshold (in place of local median) to improve traditional quantization criterion of 1D-LBP in order to improve the accuracy of 1D-LBP quantization signals. Thirdly, the strategy of quantizing component signals, PRCs, rather than the whole original signals, according to improved 1D-LBP is taken to reduce interference among signals and correctly represent fault information. Fourthly, covariance matrix of Hankel matrix of local textural signal (LTS) corresponding to each component is constructed and signals are reconstructed to reduce noise interference and dig out hidden feature information in low-dimension space. Finally, fault feature frequencies of bearings are extracted through power spectrum of reconstructed signals and the type of fault is judged. The efficiency and advantage of proposed method is verified through the comparative analysis of simulation signals, tester signals and classical methods.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008677","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":"Fixed-time anti-saturation and fault-tolerant control for quadrotor UAVs using event-trigger adaptive barrier sliding mode control.","authors":"Amin Najafi, Saleh Mobayen, Abolfazl Jalilvand","doi":"10.1016/j.isatra.2025.08.030","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.08.030","url":null,"abstract":"<p><p>This paper proposes an Adaptive Barrier Nonsingular Fixed-Time Sliding Mode Control (ABNFTSMC) scheme for quadrotor Unmanned Aerial Vehicles (UAVs). The method explicitly addresses actuator faults, input saturation, and external disturbances. A Fault Detection and Isolation (FDI) unit identifies failed rotors to maintain stability, while a Virtual Controller (VC) is used to handle instability introduced by actuator failure using inputs from functioning actuators. The Barrier Function (BF) technique identifies a stable region with high bandwidth under large disturbances. A key feature of the controller is its energy efficiency, achieved through an Event-Triggered (ET) mechanism that adapts to faults, failures, and disturbances. Additionally, this method prevents the chattering problem, extending the system's lifetime and reducing energy consumption, unlike conventional SMCs that suffer from severe chattering. By substituting the sign function with a hyperbolic tangent (HT) function, the objective has been successfully achieved. The controller efficiently alleviates actuator faults, input saturation, and high-bounded disturbances while reducing chattering. The proposed nonsingular fixed-time controller guarantees fast convergence and excellent tracking performance, as demonstrated by theoretical proofs and simulation results. The HT function helps ensure smoother performance, prolonging the life of system components. This paper provides a well-configured, power-saving approach for compensating for actuator faults and disturbances in UAVs by minimizing chattering, delivering fast response, and reducing energy consumption.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984152","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}