ISA transactionsPub Date : 2025-10-03DOI: 10.1016/j.isatra.2025.09.034
Cuauhtémoc Acosta Lúa, Stefano Di Gennaro, Ariadna Berenice Flores Jiménez, Claudia Verónica Vera Vaca
{"title":"Robust dynamic nonlinear control using adaptive gain estimation for ground vehicles under parametric uncertainties and external disturbances.","authors":"Cuauhtémoc Acosta Lúa, Stefano Di Gennaro, Ariadna Berenice Flores Jiménez, Claudia Verónica Vera Vaca","doi":"10.1016/j.isatra.2025.09.034","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.034","url":null,"abstract":"<p><p>This paper presents a robust dynamic nonlinear control strategy with adaptive gain estimation for ground vehicles equipped with Active Front Steering (AFS) and Rear Torque Vectoring (RTV). The proposed controller ensures accurate trajectory tracking despite parametric uncertainties and external disturbances by incorporating high-order sliding mode (HOSM) estimators with adaptive gains. Additionally, a novel HOSM observer, also designed with adaptive gains, reconstructs the vehicle's lateral velocity, enhancing control performance under dynamic driving conditions. The controller's effectiveness is validated through numerical simulations in CarSim, where a challenging double-lane-change test maneuver, based on the ISO 3888-2:2011 specifications, demonstrates superior transient behavior and disturbance rejection compared to conventional approaches.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254311","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":"Multidimensional fast nonlinear blind deconvolution network for bearing compound features extraction.","authors":"Hao Ma, Baokun Han, Qingyao Zhang, Jinrui Wang, Zongzhen Zhang, Huaiqian Bao","doi":"10.1016/j.isatra.2025.09.037","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.037","url":null,"abstract":"<p><p>The uneven stress distribution and abnormal load caused by a single bearing fault often lead to another new fault. The weak features of the new fault are either aliased with the existing fault features and ignored, or directly covered by irrelevant interference components. To achieve separation and extraction of compound faults, multidimensional fast nonlinear blind deconvolution network (MFNBD-net) is proposed. Firstly, fast nonlinear blind deconvolution (FNBD) is extended to MFNBD based on the principle of multi-dimensional blind deconvolution to obtain the potential of decoupling composite features. Then, uniform multidimensional initialization for indicating the convergence direction is introduced to enhance the performance of multi-feature extraction. Next, based on the uniformity of harmonic distribution, trimmed envelope spectrum kurtosis for guiding the elimination of irrelevant and repetitive components in multi-dimensional output is proposed. Finally, adaptive nonlinear transformation and filter waveform penalty are incorporated into the deconvolution process and MFNBD-net is proposed. Simulation and experiments show that MFNBD-net has advantages in multi-dimensional feature decoupling and robustness, and it is a promising composite feature extraction tool.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145246005","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":"Data-driven modeling and adaptive event-triggered secure control for autonomous vehicles subject to sensor attacks.","authors":"Hong-Tao Sun, Xinyu Xie, Miao Rong, Zongying Feng, Chen Peng","doi":"10.1016/j.isatra.2025.09.036","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.036","url":null,"abstract":"<p><p>This paper is concerned with data-driven model identification and adaptive event-triggered secure control of autonomous vehicles subject to sensor attacks. Firstly, the lateral dynamical model of autonomous vehicles is identified from data by exploiting the dynamic mode decomposition (DMD) approach and the sensor attacks are considered based on the established model. Then, an adaptive event-triggered scheme is well developed to balance the communication efficiency and control performance. Thus, the sliding-mode-like control scheme is utilized to counteract the sensor attacks. The stability analysis and stabilization design are derived using Lyapunov theory and linear matrix inequalities technique. There are three advantages of the proposed control scheme: a) DMD overcomes modeling difficulties, b) event-triggered threshold is adaptively regulated by the feedback measurement and c) the sensor attacks can be actively mitigated. At last, several comparison examples show the effectiveness of the proposed data-driven secure control scheme.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254253","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}
ISA transactionsPub Date : 2025-09-30DOI: 10.1016/j.isatra.2025.09.033
Shunping Su, Zhenkun Huang, Jinxiong Chen, Zhiyong Li
{"title":"Event-based boundary control for hyperbolic distributed parameter systems under border-DoS attacks.","authors":"Shunping Su, Zhenkun Huang, Jinxiong Chen, Zhiyong Li","doi":"10.1016/j.isatra.2025.09.033","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.033","url":null,"abstract":"<p><p>The paper investigates event-based boundary control for hyperbolic distributed parameter systems (HDPSs) under Denial-of-Service (DoS) attacks. Differently from the existing boundary control for HDPSs, this work proposes a dynamic event-triggered boundary control (DETBC) design strategy for HDPSs that can resist DoS attacks. This method not only addresses the stability issue of controlling HDPSs during DoS attacks, but also dramatically reduces the cost of sampling and control. This paper uses a DoS attack-adapted switched observer to design a DETBC mechanism, and then constructs switched HDPSs with state delay. The piecewise Lyapunov functional technique is used to investigate the exponential stability of HDPSs. A co-design scheme for controller and observer gains is proposed. Finally, a numerical example is given to verify the validity of the theoretical results.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254237","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}
ISA transactionsPub Date : 2025-09-30DOI: 10.1016/j.isatra.2025.09.039
Zhen Zhang, Yinan Guo, Song Zhu, Dunwei Gong, Feng Jiao, Xianfang Song
{"title":"Model-free and finite-time sliding-mode tracking control based on a second-order adaptive disturbance observer.","authors":"Zhen Zhang, Yinan Guo, Song Zhu, Dunwei Gong, Feng Jiao, Xianfang Song","doi":"10.1016/j.isatra.2025.09.039","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.039","url":null,"abstract":"<p><p>In practical engineering, many control issues face the challenge of being unmodelable, rendering model-based control methods inapplicable. To address this problem, an enhanced model-free and finite-time control framework incorporating a disturbance observer and sliding-mode control is put forward. Firstly, a second-order adaptive disturbance observer is constructed using tracking error. It is capable of responding in real-time to the system's tracking dynamics and adaptively estimating the lump disturbance, achieving collaborative improvement in estimation and tracking performance. This observer offers advantages a simple structure, few parameters, and wide applicability. Secondly, based on an established auxiliary strategy, a sliding-mode control law is designed using the virtual estimation state error of the proposed observer. This design simplifies the controller structure, ensures global sliding-mode robustness, and avoids sliding-mode chattering and high-frequency switching of the controller. Thirdly, a model-free and finite-time controller is developed by incorporating the lumped disturbance (estimated by the designed second-order adaptive disturbance observer) into the proposed sliding-mode control law through compensation, and its finite-time exponential convergence is theoretically proven. Finally, the effectiveness and superiority of the proposed method are verified through comparative experiments.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145260038","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}
ISA transactionsPub Date : 2025-09-30DOI: 10.1016/j.isatra.2025.09.027
Dong Xu, Yajuan Liu, Sangmoon Lee, Xiangpeng Xie
{"title":"Resilient event-triggered quasi-synchronization control for CLSs with parameter mismatches under DoS attacks.","authors":"Dong Xu, Yajuan Liu, Sangmoon Lee, Xiangpeng Xie","doi":"10.1016/j.isatra.2025.09.027","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.027","url":null,"abstract":"<p><p>This paper investigates quasi-synchronization of chaotic Lur'e systems (CLSs) with parameter mismatches under denial-of-service (DoS) attacks. A resilient memory event-triggered scheme (RMETS) is proposed to mitigate network congestion and attack-induced disruptions. Unlike conventional schemes requiring prior knowledge of attack timing, RMETS employs an acknowledgment (ACK) mechanism to detect packet loss and introduces an ACK-related performance loss term for adaptive adjustment of release probability. Historical release data are further incorporated to refine control updates at critical sampling instants, balancing communication demands with control performance. A co-design of RMETS and a memory-based controller ensures the quasi-synchronization of CLSs within a predefined error bound. The effectiveness of the proposed approach is validated through simulations using Chua's circuit.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259998","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}
ISA transactionsPub Date : 2025-09-27DOI: 10.1016/j.isatra.2025.09.031
Ji Zhao, Biao Xie, Qiang Li, Yi Yu, Guobing Qian, Hongbin Zhang
{"title":"A family of constrained maximum mixture total correntropy algorithms for adaptive filtering.","authors":"Ji Zhao, Biao Xie, Qiang Li, Yi Yu, Guobing Qian, Hongbin Zhang","doi":"10.1016/j.isatra.2025.09.031","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.031","url":null,"abstract":"<p><p>As a robust adaptive filtering algorithm, the constrained maximum total correntropy (CMTC) algorithm exhibits good filtering performance compared to existing methods, especially when the system has noisy input and output signals. However, CMTC experiences some performance degradation when using a fixed kernel bandwidth. Therefore, we propose the constrained maximum mixture total correntropy (CMMTC) algorithm, which leverages mixture correntropy to enhance flexibility by adjusting the proportion of different kernel bandwidths. In general, increasing kernel bandwidth typically leads to a reduction in the convergence speed of CMTC. Hence, based on a combined strategy, we innovatively introduce two adaptive versions of the CMMTC algorithm by considering a variable mixture coefficient. For the proposed CMMTC algorithm, under some reasonable assumptions, we have derived the mean convergence condition and the theoretical mean-square-deviation expression, which are also verified by simulation results. In comparison with other related algorithms, several experimental results demonstrate that the proposed algorithms can realize superior filtering performance.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254285","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}
ISA transactionsPub Date : 2025-09-27DOI: 10.1016/j.isatra.2025.09.030
Jaehan Jeon, Gerasimos Theotokatos
{"title":"A methodology to develop and manage data-driven models for marine engine long-term health prognosis.","authors":"Jaehan Jeon, Gerasimos Theotokatos","doi":"10.1016/j.isatra.2025.09.030","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.030","url":null,"abstract":"<p><p>This study proposes a novel methodology to develop and manage data-driven models for ship machinery Prognostics and Health Management (PHM). A four-stroke marine engine is investigated considering exhaust valve wear degradation. Simulated datasets are generated using a physics-based digital twin integrated with stochastic degradation models. Health indicators (HI) construction and forecast sub-models are developed, based on Multi-Layer Perceptron and Bayesian Neural Networks, respectively. Data-driven model management employs error and uncertainty metrics for deciding re-training of HI forecast sub-models, resulting in R<sup>2</sup> increases from 0.24 to 0.89 and from 0.26 to 0.94 in Cases 1 and 2, respectively. This is the first study that integrates thermodynamic models with stochastic degradation models to develop marine engine digital twins, while also introducing data-driven model management, thus contributing to the PHM system adoption by the maritime industry.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145260347","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 neural dynamic event-triggered mechanism for adaptive sliding mode control of nonlinear networked Markovian jump systems.","authors":"Yiming Yang, Dongyu Liu, Baoping Jiang, Hamid Reza Karimi","doi":"10.1016/j.isatra.2025.09.023","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.023","url":null,"abstract":"<p><p>This paper addresses the adaptive sliding mode control problem for a class of nonlinear networked Markovian jump systems based on event-triggered observers. First, a neural network-based event-triggered mechanism is proposed to integrate with the designed observer. Second, a novel integral sliding surface function is designed, and the corresponding sliding mode dynamics and error dynamics are derived. Third, to address the nonlinear disturbances and malicious attacks within the system, an adaptive compensator is proposed to ensure system security. Furthermore, an observer-based event-triggered sliding mode controller is designed to ensure finite-time convergence to the predefined sliding mode surface. Fourth, based on the determined transition rates, it is proven that the sliding mode dynamics exhibit stochastic stability with a prescribed H<sub>∞</sub> performance level in terms of linear matrix inequality method, and it is also shown that Zeno behavior is excluded. Finally, the effectiveness of the control scheme is verified by simulation using a single-link manipulator model.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145246002","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}
ISA transactionsPub Date : 2025-09-27DOI: 10.1016/j.isatra.2025.09.035
Jian Li, Yunfeng Wang, He Ren, Qingyu Su
{"title":"Dynamic load altering attack detection in cyber physical power system based on improved Kalman/H<sub>∞</sub> co-filtering.","authors":"Jian Li, Yunfeng Wang, He Ren, Qingyu Su","doi":"10.1016/j.isatra.2025.09.035","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.035","url":null,"abstract":"<p><p>This paper proposes an attack detection scheme for closed-loop Dynamic Load Altering Attacks (DLAA) in Cyber Physical Power Systems (CPPSs). It aims to improve the accuracy of state estimation and attack detection in CPPSs in the presence of D-LAA and noise disturbances. First, a discrete-time CPPSs model subject to D-LAA and unknown-statistics noise is constructed to capture the system dynamics under the influence of cyberattacks and disturbances. Second, a state estimation method based on an improved Kalman/H<sub>∞</sub> co-filter is proposed, in which the multi-fading factor adaptive Kalman filter (MFAKF) is used to handle Gaussian noise with unknown-statistics, and the H<sub>∞</sub> filter is used to enhance robustness against non-Gaussian disturbances. Finally, a detection algorithm based on cosine similarity matching is designed to identify anomalies by calculating the angular deviation between the estimated and measured states. Simulation results show that for the state ω<sub>1</sub> in the IEEE 3-machine 6-bus system, the proposed MFAKF-HF reduces the RMSE by 75% relative to MFAKF and 62% relative to H<sub>∞</sub> filtering, demonstrating the improved accuracy and robustness of the proposed estimation and detection scheme under both attack and noise conditions.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254275","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}