ISA transactionsPub Date : 2025-07-12DOI: 10.1016/j.isatra.2025.07.021
Adel Afia , Fawzi Gougam , Abdenour Soualhi , Mohammed Wadi , Mohamed Tahi , Mohammed Amine Sahraoui
{"title":"A data driven fault diagnosis approach for robotic cutting tools in smart manufacturing","authors":"Adel Afia , Fawzi Gougam , Abdenour Soualhi , Mohammed Wadi , Mohamed Tahi , Mohammed Amine Sahraoui","doi":"10.1016/j.isatra.2025.07.021","DOIUrl":"10.1016/j.isatra.2025.07.021","url":null,"abstract":"<div><div>In smart manufacturing within Industry 4.0, tool condition monitoring (TCM) is used to improve productivity and machine availability by leveraging advanced sensors and computational intelligence to prevent tool damage. This paper develops a hybrid methodology using heterogeneous sensor measurements for monitoring robotic cutting tools with four tool states: healthy, surface damage, flake damage and broken tooth. The proposed approach integrates the maximal overlap discrete wavelet packet transform (MODWPT) with health indicators to construct feature matrices for each tool state. Feature selection is performed using the tree growth algorithm (TGA) to reduce computation time and improve feature space separation by selecting only relevant features. The selected features are input into a Gaussian mixture model (GMM) to detect, identify and classify each tool state with high accuracy. The proposed method provides a classification accuracy of 99.04 % for vibration, 95.51 % for torque, and 91.67 % for force signals. Using unseen vibration data, the model achieved a test accuracy of 98.44 %, demonstrating a high degree of generalizability. Comparative analysis demonstrates that our proposed approach provides superior feature discrimination and model stability, balancing computational efficiency and classification accuracy, validating the TGA-GMM framework as an effective solution for tool fault diagnosis in noisy, high-dimensional data.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 280-297"},"PeriodicalIF":6.5,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144651663","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}
{"title":"Immersion and invariance adaptive controller and mixer for coaxial tilt-rotor UAV","authors":"Longlong Chen , Yanmei Jia , Sihao Sun , Zongyang Lv , Yuhu Wu","doi":"10.1016/j.isatra.2025.07.015","DOIUrl":"10.1016/j.isatra.2025.07.015","url":null,"abstract":"<div><div>This study presents a motion control system for a coaxial tilt-rotor (CTR) unmanned aerial vehicle (UAV) equipped with two CTR modules and a tail rotor. The existing adaptive control strategies for CTRUAVs fail to guarantee the theoretical convergence of estimated parameters to their true values. Additionally, the existing mixer requires frequent and inefficient adjustments of the tilt angles for motion control. To address these issues, this work proposes a control strategy that integrates a robust integral of the sign of the error (RISE)-based immersion and invariance (I&I) adaptive controller with segmented gains and an improved mixer. The RISE-based adaptive controller is theoretically capable of estimating and compensating for external disturbance torques and forces with bounded derivatives. Furthermore, a model of the CTR module that accounts for differences between the upper and lower rotors is introduced, and the proposed mixer is designed to realize efficient control at varying tilt angles of the CTR modules. Experimental results demonstrate that the proposed control scheme significantly improves stability, transient response speed, disturbance rejection performance, and parameter estimation accuracy compared to existing control strategies for the CTRUAV.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 353-363"},"PeriodicalIF":6.5,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661441","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}
ISA transactionsPub Date : 2025-07-12DOI: 10.1016/j.isatra.2025.07.016
Chong Liu , Leiming Wang , Zhousheng Chu , Hanguang Su
{"title":"Neural network-based adaptive decentralized safe control for interconnected nonlinear systems with time delays","authors":"Chong Liu , Leiming Wang , Zhousheng Chu , Hanguang Su","doi":"10.1016/j.isatra.2025.07.016","DOIUrl":"10.1016/j.isatra.2025.07.016","url":null,"abstract":"<div><div>This paper addresses the safety control issue for interconnected nonlinear systems with time delays and asymmetric input constraints by proposing a decentralized dynamic event-triggered (DET) controller based on the adaptive dynamic programming (ADP) method. Unlike other studies on large-scale interconnected systems, the equilibrium point of the system under our study is not zero. Firstly, by incorporating a discount factor and introducing a barrier function and a Lyapunov–Krasovskii (L-K) function, we construct a cost function for the interconnected system with a non-zero equilibrium point, time delay, and constraints, thereby transforming the constrained decentralized control problem into an unconstrained optimal control problem (OCP). Subsequently, an event-based Hamilton–Jacobi–Bellman (HJB) equation is established. To enhance computational efficiency, a DET mechanism is proposed. Then, the event-triggered HJB equation is solved utilizing the learning method based on ADP. Simultaneously, the weights of the neural network (NN) are optimized using a gradient descent algorithm and experience replay (ER) techniques. By employing ER technology, we have eliminated the system’s requirement for continuous excitation. Furthermore, through theoretical analysis, we have demonstrated the uniform ultimate boundedness (UUB) of the system states and neural network weights, and excluded Zeno behavior. Finally, the effectiveness of the proposed method is validated by using a spring-pendulum example.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 168-178"},"PeriodicalIF":6.5,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144719289","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}
ISA transactionsPub Date : 2025-07-12DOI: 10.1016/j.isatra.2025.07.023
Zhendong Yin , Li Wang , Xianqun Qiu , Jiyong Zhang
{"title":"Feedback chaotic growth optimizer for parameter extraction of a novel direct current arc model","authors":"Zhendong Yin , Li Wang , Xianqun Qiu , Jiyong Zhang","doi":"10.1016/j.isatra.2025.07.023","DOIUrl":"10.1016/j.isatra.2025.07.023","url":null,"abstract":"<div><div>Direct current (DC) arc faults are a leading cause of fire incidents in photovoltaic (PV) systems. Accurate modeling of DC arc faults is essential for understanding the underlying mechanisms of DC arcs and for developing effective detection strategies. In this study, we propose a novel model for DC arcs, referred to as the exponent segmented noise model. This model effectively characterizes arc noise by establishing an exponential relationship between frequency values and spectral energy. To enable precise parameter extraction from the exponent segmented noise model, we introduce a new metaheuristic algorithm called the feedback chaotic growth optimizer (FCGRO). FCGRO improves upon the traditional growth optimizer (GRO) by integrating feedback operators and chaos mechanisms. Firstly, the convergence performance of FCGRO is rigorously evaluated through comparative experiments on three well-established benchmark engineering optimization problems. Subsequently, based on data collected from an established experimental platform, the proposed FCGRO and eight state-of-the-art algorithms are employed to extract parameters of the exponent segmented noise model for DC arc faults. The FCGRO achieves an overall average root mean square error (RMSE) of 0.0418 with a standard deviation of 0.00818, representing reductions of at least 10.43 % and 26.86 %, respectively, compared to the other eight methods. These results indicate that FCGRO delivers more accurate and stable parameter estimations than the competing algorithms. Regarding computational efficiency, FCGRO has an average processing time of 9.969 s, ranking it third among the nine evaluated methods, which confirms its competitiveness in terms of speed. Finally, compared with existing DC arc models, the proposed exponent segmented noise model reduces RMSE by an average of 53.26 %, demonstrating its superior modeling capability.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 364-378"},"PeriodicalIF":6.5,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692843","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}
ISA transactionsPub Date : 2025-07-11DOI: 10.1016/j.isatra.2025.07.020
Jintao Zhao , Tao Liu , Junhao Huang
{"title":"Enhanced obstacle avoidance for autonomous underwater vehicles via path integral control based on guiding vector field","authors":"Jintao Zhao , Tao Liu , Junhao Huang","doi":"10.1016/j.isatra.2025.07.020","DOIUrl":"10.1016/j.isatra.2025.07.020","url":null,"abstract":"<div><div><span><span><span>Autonomous Underwater Vehicles (AUVs) face significant challenges in tracking, navigation, and obstacle avoidance—critical aspects for advancing intelligent underwater robotics. This research presents a new navigation technique that combines Guiding Vector Field (GVF) concepts with Model Predictive Path Integral (MPPI) control to improve the precision and efficiency of vectored </span>thruster AUV operating in complex environments. The proposed approach utilizes the AUV's relative positioning and environmental data to generate </span>obstacle avoidance trajectories as desired GVF. Subsequently, MPPI optimization is applied to control inputs, considering dynamic constraints, to achieve effective tracking and obstacle avoidance. Extensive simulation experiments demonstrate the method's efficacy in navigating complex scenarios with non-convex obstacles. In the aspect of path tracking, the tracking error is reduced by 64 %, while maintaining safe distances in various obstacle configurations. Results show that the integrated method successfully combines local optimization prediction capabilities of MPPI with the global velocity planning of GVF, enabling efficient AUV navigation in intricate environments while ensuring the effectiveness and safety of the execution process. The method demonstrates robust performance even under disturbance conditions, maintaining a tracking error of only 0.017 m. This research contributes a solution for AUV operation in challenging maritime settings, with applications in marine surveying, underwater </span>search and rescue<span>, and offshore operations<span>. By addressing key challenges in underwater navigation, this study advances the practical capabilities of AUV technology, paving the way for more efficient and reliable underwater robotic systems.</span></span></div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 116-125"},"PeriodicalIF":6.5,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144644398","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}
ISA transactionsPub Date : 2025-07-11DOI: 10.1016/j.isatra.2025.07.008
Lifan Li, Lina Yao, Yaoqiang Wang
{"title":"Minimum rational entropy fault-tolerant control for nonlinear stochastic distribution control systems with quantized signals","authors":"Lifan Li, Lina Yao, Yaoqiang Wang","doi":"10.1016/j.isatra.2025.07.008","DOIUrl":"10.1016/j.isatra.2025.07.008","url":null,"abstract":"<div><div>The fault-tolerant control (FTC) issue for quantized nonlinear stochastic distribution control (SDC) systems in the presence of both actuator and sensor faults is addressed. A two-step fuzzy modeling approach is employed to systematically construct the static and dynamic models of the system, which establishes a foundational framework for subsequent fault diagnosis (FD) and FTC. Building upon the model, an adaptive augmented observer is designed to estimate actuator and sensor faults simultaneously, even under the influence of quantization effects. Furthermore, an innovative comprehensive FTC strategy is proposed, in which a virtual sensor compensator is integrated with a minimum rational entropy (MRE) fault-tolerant controller to effectively compensate for faults and ensure the system stability. The practical effectiveness of the proposed methodology is validated through its application to a molecular weight distribution system.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 159-167"},"PeriodicalIF":6.5,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669171","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}
ISA transactionsPub Date : 2025-07-10DOI: 10.1016/j.isatra.2025.06.018
Mohammad Soleymani, Nooshin Bigdeli, Mehdi Rahmani
{"title":"Real-time random reference tracking nonlinear model predictive control: a case study on wind turbines","authors":"Mohammad Soleymani, Nooshin Bigdeli, Mehdi Rahmani","doi":"10.1016/j.isatra.2025.06.018","DOIUrl":"10.1016/j.isatra.2025.06.018","url":null,"abstract":"<div><div><span><span><span>Recently, a research effort to extend nonlinear model<span> predictive control methods from setpoint stabilization to reference tracking has been felt increasingly. On the other hand, uncertainty in the reference signal and the requirement for its dynamic forecasting in applications such as </span></span>wind turbine<span> control motivate the need for robust tracking nonlinear model predictive control<span> approaches more and more. Therefore, this study proposes a random reference tracking nonlinear model predictive control<span> with dynamic forecasting of stochastic references. Convergence to a robust invariant set is guaranteed by an additional constraint limiting the previous step’s tracking stage </span></span></span></span>cost function<span>. The proposed predictive approach is implemented using a parallel Newton-type method to make it more efficient and applicable. The proposed approach for wind turbine control is designed considering the random </span></span>wind speed<span> reference. Simulations are performed for extreme and fatigue load scenarios. The results show that the proposed controller performs more robustly than the nominal nonlinear model predictive control approach, performing better in optimal power extraction and reducing aerodynamic loads.</span></div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"165 ","pages":"Pages 170-182"},"PeriodicalIF":6.5,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621605","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}
ISA transactionsPub Date : 2025-07-09DOI: 10.1016/j.isatra.2025.07.018
Xiangtang Zhao, Zhigang Zhao, Cheng Su
{"title":"Spatial multi-vector and multi-rigid-body obstacle avoidance planning for multi-robot coordinated suspension system","authors":"Xiangtang Zhao, Zhigang Zhao, Cheng Su","doi":"10.1016/j.isatra.2025.07.018","DOIUrl":"10.1016/j.isatra.2025.07.018","url":null,"abstract":"<div><div><span><span>Multi-robot coordinated suspension systems (MCSS) face challenges such as difficulties in decoupling due to strong coupling in multi-body dynamics, computational complexity explosion caused by high-dimensional state spaces, and a scarcity of obstacle avoidance planning methods for multi-rigid-body systems. To address these issues, the telescopic pyramidal configuration (TPC) and the multi-strategy geyser-inspired algorithm (MGEA) are proposed. These methods enable multi-vector and multi-rigid-body obstacle avoidance planning via a hierarchical-search and step-optimization (HSSO) framework. The MGEA enhances global search capabilities through chaotic mapping initialization, </span>Lévy flights, differential evolution, and stability constraints, while hierarchical cooperative planning ensures the prevention of cable </span>entanglement and decouples multi-robot motion. Simulation and experimental results show that MGEA outperforms benchmark algorithms, achieving a 16.35 % reduction in trajectory length, a 13.74 % increase in computational speed, and an 18.60 % improvement in minimum fitness, while maintaining zero collisions in cluttered 3D environments. This method provides an efficient solution for industrial lifting tasks and demonstrates scalability potential. These advancements establish a theoretical foundation for real-time planning in dynamic non-convex environments, addressing critical challenges in the application of multi-robot suspension systems.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 337-352"},"PeriodicalIF":6.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144644455","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}
ISA transactionsPub Date : 2025-07-09DOI: 10.1016/j.isatra.2025.07.006
Weiwei Lin, Jiajun Wang, Xiaoling Wang, Jun Zhang, Haojun Gao
{"title":"Multi-source positioning information fusion method based on improved robust Kalman filter","authors":"Weiwei Lin, Jiajun Wang, Xiaoling Wang, Jun Zhang, Haojun Gao","doi":"10.1016/j.isatra.2025.07.006","DOIUrl":"10.1016/j.isatra.2025.07.006","url":null,"abstract":"<div><div>Enhancing positioning accuracy in rolling machinery is vital for quality and construction efficiency. To mitigate random noise interference in deep and narrow valleys, a multi-source positioning information fusion method utilizing an improved robust Kalman filter<span><span><span> is proposed. This method adaptively selects optimal observations from GNSS, Robotic Total Station (RTS) and </span>Ultra Wide Band<span> (UWB) data, compensates for location deviation and data loss from noise interference, thus improving data robustness. The Kalman filter is improved by incorporating a thick tail Laplace distribution to dynamically adjust noise covariance, overcoming challenges with large </span></span>random errors<span> in data fusion and improving the robustness. Engineering tests show this method can adapt to complex and harsh environments in deep and narrow river valleys, with a compensation rate of over 97.33 % for data offset and loss issues, reducing localization offset rates by 7.72 % and loss rates by 1.64 % compared to single-method approaches, effectively improving the robustness, accuracy, and completeness of real-time monitoring results.</span></span></div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 429-444"},"PeriodicalIF":6.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144628340","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}
ISA transactionsPub Date : 2025-07-09DOI: 10.1016/j.isatra.2025.07.007
Yunkai Wu , Zefan Zhu , Peng Shi , Yueyang Li
{"title":"Active fault diagnosis for AUV over-actuated systems based on UIOs and control allocation","authors":"Yunkai Wu , Zefan Zhu , Peng Shi , Yueyang Li","doi":"10.1016/j.isatra.2025.07.007","DOIUrl":"10.1016/j.isatra.2025.07.007","url":null,"abstract":"<div><div>The navigation performance of autonomous underwater vehicles (AUVs) relies mainly on the propulsion system, which makes the study of the safety and reliability of the propulsion system highly significant. This paper investigates an over-actuated AUV propulsion system with six degrees of freedom and presents an active fault diagnosis framework that combines unknown input observers (UIO) with control allocation. The simulation results show that the proposed integrated methodology successfully performs fault detection, magnitude estimation, and isolation for AUV over-actuated systems. In particular, since no auxiliary signals are added, it is possible to ensure normal operation of the system by only internally adjusting the allocation of the original inputs.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"166 ","pages":"Pages 80-88"},"PeriodicalIF":6.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144651664","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}