{"title":"PCE-based uncertain PWA modeling and control for DMHP mode transition system.","authors":"Cong Liang, Huayang Sun, Xing Xu, Feng Wang, Zhiguang Zhou","doi":"10.1016/j.isatra.2025.09.026","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.026","url":null,"abstract":"<p><p>The parameters of powertrain systems exhibit random uncertainties due to manufacturing variations, component friction and wear over time. These uncertainties, coupled with the highly nonlinear dynamics of hybrid powertrains, can lead to significant changes in system dynamics and adversely affect the smoothness and quality of mode transition process (MTP). This paper focuses on investigating the impact of parameter uncertainties on MTP performance in a dual-motor hybrid powertrain (DMHP) and proposes a corresponding coordinated control strategy. Firstly, local and global sensitivity analyses are conducted to identify the key powertrain parameters that significantly affect mode transition performance. Then, considering the uncertainties of key parameters, polynomial chaos expansion (PCE) method is adopted and the uncertain piecewise-affine (PWA) model of MTP can be transformed into a deterministic system. Finally, a PWA-PCE H<sub>2</sub> coordinated control strategy is designed to achieve robust smooth mode transitions. Simulation and hardware-in-the-loop (HiL) test results demonstrate that the proposed control strategy significantly enhances the capability of system to handle parameter uncertainties, thereby maintaining a high-quality MTP under uncertain conditions.</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":"145294790","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}
{"title":"Robust and non-asymptotic state estimation for MIMO descriptor systems.","authors":"Jie Liu, Da-Yan Liu, Driss Boutat, Ze-Hao Wu, Feiqi Deng, Zhiliang Zhao","doi":"10.1016/j.isatra.2025.09.022","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.022","url":null,"abstract":"<p><p>In this research paper, a state estimation framework for a class of descriptor linear systems with MIMO is provided by using auxiliary modulating dynamical systems. First, the considered model is transformed into a simpler form involving the derivatives of inputs and outputs, based on which the auxiliary systems are applied. Then, the state variables are expressed through modulating integrals without the need for initial conditions, guaranteeing non-asymptotic convergence within fixed-time. This framework does not require the calculation of the derivatives of noisy outputs in discrete cases, reducing sensitivity to high-frequency noise in the estimation. Finally, the performance of the proposed method is validated through numerical simulations, which provide practical insights into its effectiveness and enable a comparison with some observers.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228667","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":"Optimized voltage vector selection for dual-star induction motor: Robust predictive direct torque control-based hysteresis-free approach.","authors":"Amel Kasri, Kamel Ouari, Youcef Belkhier, Djamel Ziane, Mohamed Fouad Benkhoris, Mohamed Benbouzid","doi":"10.1016/j.isatra.2025.09.015","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.09.015","url":null,"abstract":"<p><p>The dual-star induction machine is a widely adopted multiphase machine in industrial applications, thanks to its superior reliability in managing power supply faults and enhanced robustness. This study presents a robust predictive DTC strategy for a dual-star induction motor supplied by dual-voltage source inverters. Relying on a cost function optimization, the suggested predictive DTC algorithm replaces traditional hysteresis regulators and switching tables typically employed in classical DTC, determining the optimal sequence of voltage space vectors. Regarding speed regulation, the proposed MPC framework incorporates integral action, eliminating steady-state inaccuracies and improving disturbance rejection under model uncertainties and external perturbations. Real-time validation on the OPAL-RT platform confirms the effectiveness of the proposed scheme. Compared with conventional DTC, torque and flux ripples are reduced by 83.95 % and 74.75 %, respectively, while current THD decreases by 77.89 %. In addition, the speed response time improves by 82.5 %, and the rejection time by 97 %. These results highlight the robustness and efficiency of the proposed RPDTC technique, making it a strong candidate for high-performance DSIM drive applications.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228649","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}