Pub Date : 2026-02-01Epub Date: 2025-11-11DOI: 10.1016/j.jfranklin.2025.107936
Srinidhi A , Raja R , Huang T , Niezabitowski M , Xinzhi Liu
This study concentrates on the admissibility analysis of descriptor half vehicle suspension system by means of Retarded Sampled Data Control (RSDC) under delayed state fragmentation groundwork. The descriptor form of the half vehicle suspension system is modelled first which describes simultaneously both the static and dynamic behaviour of the system. For the first time, an enhanced delay fragmentation based looped Lyapunov functional is proposed for the singular half-car suspension, which yields promising results in reducing the conservatism of the stability criteria. This approach fully exploits the dynamic features of the current sampling sequence and fragmented delay states. Additionally, a new integral inequality specific to singular system is derived to ensure stability under the prescribed performance index. Finally numerical simulations validate the feasibility and effectiveness of the proposed approach under the maximum sampling time.
{"title":"Delayed state fragmentation approach for descriptor modeling of half vehicle suspension under retarded sampled data control: An admissibility analysis","authors":"Srinidhi A , Raja R , Huang T , Niezabitowski M , Xinzhi Liu","doi":"10.1016/j.jfranklin.2025.107936","DOIUrl":"10.1016/j.jfranklin.2025.107936","url":null,"abstract":"<div><div>This study concentrates on the admissibility analysis of descriptor half vehicle suspension system by means of Retarded Sampled Data Control (RSDC) under delayed state fragmentation groundwork. The descriptor form of the half vehicle suspension system is modelled first which describes simultaneously both the static and dynamic behaviour of the system. For the first time, an enhanced delay fragmentation based looped Lyapunov functional is proposed for the singular half-car suspension, which yields promising results in reducing the conservatism of the stability criteria. This approach fully exploits the dynamic features of the current sampling sequence and fragmented delay states. Additionally, a new integral inequality specific to singular system is derived to ensure stability under the prescribed performance index. Finally numerical simulations validate the feasibility and effectiveness of the proposed approach under the maximum sampling time.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 107936"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-11DOI: 10.1016/j.jfranklin.2026.108404
Chen Zhou , Hui Ye , Yizhen Meng , Xin Tian , Yang Tao
This study proposes an innovative fault detection method for unmanned surface vehicles (USVs), integrating supervised and unsupervised learning to significantly enhance the fault detection rate (FDR) and reduce the false alarm rate (FAR). The core innovation lies in designing a reversible bridging network that efficiently fuses the residual features of unsupervised and supervised models.
By analyzing multimodal fault characteristics, both unsupervised and supervised neural network models are constructed. The unsupervised model generates residual signals by minimizing reconstruction errors, while the supervised model produces feature residual signals by optimizing the loss function. The reversible bridging network merges the two types of residual features, significantly improving detection accuracy and robustness.
Simulation experiments demonstrate that the hybrid model achieves a fault detection rate of 94.65%, far exceeding the performance of using only unsupervised or supervised models, with a false alarm rate of only 1.15%. This method provides a new technical approach for USV fault diagnosis in complex scenarios, holding significant theoretical and practical application value.
{"title":"Fault Detection of Unmanned Surface Vehicles Based on the Combination of Supervised and Unsupervised Models","authors":"Chen Zhou , Hui Ye , Yizhen Meng , Xin Tian , Yang Tao","doi":"10.1016/j.jfranklin.2026.108404","DOIUrl":"10.1016/j.jfranklin.2026.108404","url":null,"abstract":"<div><div>This study proposes an innovative fault detection method for unmanned surface vehicles (USVs), integrating supervised and unsupervised learning to significantly enhance the fault detection rate (FDR) and reduce the false alarm rate (FAR). The core innovation lies in designing a reversible bridging network that efficiently fuses the residual features of unsupervised and supervised models.</div><div>By analyzing multimodal fault characteristics, both unsupervised and supervised neural network models are constructed. The unsupervised model generates residual signals by minimizing reconstruction errors, while the supervised model produces feature residual signals by optimizing the loss function. The reversible bridging network merges the two types of residual features, significantly improving detection accuracy and robustness.</div><div>Simulation experiments demonstrate that the <strong>hybrid model</strong> achieves a fault detection rate of 94.65%, far exceeding the performance of using only unsupervised or supervised models, with a false alarm rate of only 1.15%. This method provides a new technical approach for USV fault diagnosis in complex scenarios, holding significant theoretical and practical application value.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108404"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a fixed-time control strategy based on prescribed performance function (PPF) and tan-type Barrier Lyapunov Function (tan-type BLF) is proposed for full-state constrained Autonomous Underwater Vehicle (AUV) considering input time delay. A prescribed performance function and a tan-type BLF are designed for the errors to prevent states from violating constraints, which guarantee the transient and steady state performance of the errors. A virtual control scheme is introduced to solve the singularity problem. The complexity explosion problem is resolved by employing a fixed-time differentiator, which simplifies the computational process and reduces the number of control parameters required. In addition, a radial basis function neural network (RBFNN) is used to estimate external disturbances and model uncertainties. It is proved through the fixed-time stability theory that the proposed control strategy ensures that the errors converge to a small neighborhood near the origin in fixed time considering time delay. Finally, simulation results and comparisons are presented to demonstrate the effectiveness and superiority of the proposed strategy.
{"title":"Fixed-time full-state constrained control considering time delay of autonomous underwater vehicle based on prescribed performance and tan-type barrier Lyapunov function","authors":"Yuyang Wang, Yanchao Sun, Huanzhe Zhang, Yipeng Zhao, Shuao Cui, Hongde Qin","doi":"10.1016/j.jfranklin.2025.108385","DOIUrl":"10.1016/j.jfranklin.2025.108385","url":null,"abstract":"<div><div>In this paper, a fixed-time control strategy based on prescribed performance function (PPF) and tan-type Barrier Lyapunov Function (tan-type BLF) is proposed for full-state constrained Autonomous Underwater Vehicle (AUV) considering input time delay. A prescribed performance function and a tan-type BLF are designed for the errors to prevent states from violating constraints, which guarantee the transient and steady state performance of the errors. A virtual control scheme is introduced to solve the singularity problem. The complexity explosion problem is resolved by employing a fixed-time differentiator, which simplifies the computational process and reduces the number of control parameters required. In addition, a radial basis function neural network (RBFNN) is used to estimate external disturbances and model uncertainties. It is proved through the fixed-time stability theory that the proposed control strategy ensures that the errors converge to a small neighborhood near the origin in fixed time considering time delay. Finally, simulation results and comparisons are presented to demonstrate the effectiveness and superiority of the proposed strategy.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108385"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-09DOI: 10.1016/j.jfranklin.2026.108406
José A. Andrade-Lucio, Oscar G. Ibarra-Manzano, Miguel A. Vázquez-Olguín, Yuriy S. Shmaliy
Robust H∞ filtering has been developed using the transfer function approach to provide estimates with guaranteed energy-to-energy performance. In this paper, we use a previously proven bounded real lemma corresponding to the backward Euler method-based disturbed models and show how to numerically compute the bias correction gain K for the recursive H∞ filter, which is uniquely responsible for its performance. The unknown disturbance is viewed as a Gauss-Markov sequence with an uncertain coloredness factor. Since the error covariance is a quadratic function of K, two theorems are proved and two algorithms are developed to compute K using a linear matrix inequality. A comparison of the H∞, Kalman, and unbiased finite impulse response (UFIR) filters is provided in terms of mean square error, robustness, and estimation quality. It is shown numerically and experimentally that the gain K of the H∞ filter is between the Kalman gain and the UFIR filter gain, and that under certain conditions the H∞ filter can outperform both of them.
{"title":"Recursive H∞ filtering: Computing gain using LMI for backward Euler method-based disturbed models","authors":"José A. Andrade-Lucio, Oscar G. Ibarra-Manzano, Miguel A. Vázquez-Olguín, Yuriy S. Shmaliy","doi":"10.1016/j.jfranklin.2026.108406","DOIUrl":"10.1016/j.jfranklin.2026.108406","url":null,"abstract":"<div><div>Robust <em>H</em><sub>∞</sub> filtering has been developed using the transfer function approach to provide estimates with guaranteed <em>energy-to-energy</em> performance. In this paper, we use a previously proven bounded real lemma corresponding to the backward Euler method-based disturbed models and show how to numerically compute the bias correction gain <strong>K</strong> for the recursive <em>H</em><sub>∞</sub> filter, which is uniquely responsible for its performance. The unknown disturbance is viewed as a Gauss-Markov sequence with an uncertain coloredness factor. Since the error covariance is a quadratic function of <strong>K</strong>, two theorems are proved and two algorithms are developed to compute <strong>K</strong> using a linear matrix inequality. A comparison of the <em>H</em><sub>∞</sub>, Kalman, and unbiased finite impulse response (UFIR) filters is provided in terms of mean square error, robustness, and estimation quality. It is shown numerically and experimentally that the gain <strong>K</strong> of the <em>H</em><sub>∞</sub> filter is between the Kalman gain and the UFIR filter gain, and that under certain conditions the <em>H</em><sub>∞</sub> filter can outperform both of them.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108406"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1016/j.jfranklin.2025.108391
Shouting Hong , Haoyue Yang , Tarek Raïssi , Junfeng Zhang
This paper investigates the dual-synchronization problem of fuzzy positive Markovian jump complex networks with dynamic links based on double observations. A class of fuzzy positive Markovian jump complex networks is established by introducing dynamic links between nodes. Subsequently, a controller and the corresponding link coupling term are designed to achieve the positive and synchronous of the node systems and the link systems. Then, a synchronization strategy is proposed based on the observations of node and link states. The main contributions are as follows: (i) A dual-synchronization framework is constructed for both nodes and links by designing the controller and the coupling term, (ii) A synchronization control strategy is proposed based on double observers of node subsystems and link subsystems, and (iii) A manageable approach is developed for design and analysis by employing linear programming and constructing co-positive Lyapunov functions. Finally, the effectiveness and feasibility of the proposed approaches are illustrated via simulation examples.
{"title":"Double observers-based node and link synchronization of fuzzy Markovian jump positive complex networks","authors":"Shouting Hong , Haoyue Yang , Tarek Raïssi , Junfeng Zhang","doi":"10.1016/j.jfranklin.2025.108391","DOIUrl":"10.1016/j.jfranklin.2025.108391","url":null,"abstract":"<div><div>This paper investigates the dual-synchronization problem of fuzzy positive Markovian jump complex networks with dynamic links based on double observations. A class of fuzzy positive Markovian jump complex networks is established by introducing dynamic links between nodes. Subsequently, a controller and the corresponding link coupling term are designed to achieve the positive and synchronous of the node systems and the link systems. Then, a synchronization strategy is proposed based on the observations of node and link states. The main contributions are as follows: (i) A dual-synchronization framework is constructed for both nodes and links by designing the controller and the coupling term, (ii) A synchronization control strategy is proposed based on double observers of node subsystems and link subsystems, and (iii) A manageable approach is developed for design and analysis by employing linear programming and constructing co-positive Lyapunov functions. Finally, the effectiveness and feasibility of the proposed approaches are illustrated via simulation examples.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108391"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model Predictive Control (MPC) has become a powerful framework for optimizing system performance under constraints. However, when applied to nonlinear systems subject to unknown but bounded uncertainties (UBB), conventional MPC approaches face significant challenges related to computational complexity and robustness. This paper proposes a robust tube-based economic model predictive control (REMPC) method using a linear parameter-varying (LPV) approach for nonlinear systems with unknown but bounded uncertainty, based on nominal predictions. Using a nonlinear embedding approach, the nonlinear model is transformed into an LPV model. The optimal states and inputs found from solving the previous optimization problem are used to estimate the scheduling variables along the prediction horizon while executing the receding horizon strategy. This approach converts the nonlinear optimization problem into a quadratic optimization problem, effectively reducing computational time by leveraging the efficiency inherent in the LPV formulation. Recursive feasibility and input-to-state stability are guaranteed. Recursive feasibility is ensured by tighter constraints, which are computed online using a zonotopic approach based on the disturbance reachable sets. A gain-scheduling H∞ controller is employed as the local controller to further tighten these constraints. The stability of the proposed approach is ensured by forcing the terminal state to converge towards the optimal equilibrium or working point of the system. Moreover, the terminal constraint is relaxed by using a constraint set around the terminal state instead of a constraint value and adding a penalty on the terminal state in the cost function. Additionally, strict dissipativity is established as a sufficient condition to prove stability. Finally, the effectiveness of the LPV-based REMPC strategy is demonstrated by controlling an isothermal Continuous Stirred Tank Reactor (CSTR), and an REMPC-LPV-based planning approach for a 1/10 scale autonomous remote-controlled (RC) electric car is also tested through simulations.
{"title":"Robust tube-based economic model predictive control of nonlinear systems using linear parameter varying approach","authors":"Heithem Boufrioua , Boubekeur Boukhezzar , Vicenç Puig","doi":"10.1016/j.jfranklin.2026.108409","DOIUrl":"10.1016/j.jfranklin.2026.108409","url":null,"abstract":"<div><div>Model Predictive Control (MPC) has become a powerful framework for optimizing system performance under constraints. However, when applied to nonlinear systems subject to unknown but bounded uncertainties (UBB), conventional MPC approaches face significant challenges related to computational complexity and robustness. This paper proposes a robust tube-based economic model predictive control (REMPC) method using a linear parameter-varying (LPV) approach for nonlinear systems with unknown but bounded uncertainty, based on nominal predictions. Using a nonlinear embedding approach, the nonlinear model is transformed into an LPV model. The optimal states and inputs found from solving the previous optimization problem are used to estimate the scheduling variables along the prediction horizon while executing the receding horizon strategy. This approach converts the nonlinear optimization problem into a quadratic optimization problem, effectively reducing computational time by leveraging the efficiency inherent in the LPV formulation. Recursive feasibility and input-to-state stability are guaranteed. Recursive feasibility is ensured by tighter constraints, which are computed online using a zonotopic approach based on the disturbance reachable sets. A gain-scheduling <em>H</em><sub>∞</sub> controller is employed as the local controller to further tighten these constraints. The stability of the proposed approach is ensured by forcing the terminal state to converge towards the optimal equilibrium or working point of the system. Moreover, the terminal constraint is relaxed by using a constraint set around the terminal state instead of a constraint value and adding a penalty on the terminal state in the cost function. Additionally, strict dissipativity is established as a sufficient condition to prove stability. Finally, the effectiveness of the LPV-based REMPC strategy is demonstrated by controlling an isothermal Continuous Stirred Tank Reactor (CSTR), and an REMPC-LPV-based planning approach for a 1/10 scale autonomous remote-controlled (RC) electric car is also tested through simulations.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108409"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents an optimized bioinspired neurodynamic control framework for the formation placement and recovery control of traffic cone robots (TCRs) under constrained control inputs. A dynamic error model is constructed based on positional states, upon which a backstepping controller is designed and integrated with a bioinspired neurodynamic module to mitigate infeasible control commands arising from large initial deviations, ensuring actuator feasibility. Lyapunov-based analysis demonstrates closed-loop stability and guarantees the asymptotic convergence of formation errors. In addition, a multi-parameter optimization framework grounded in noncooperative game theory is proposed to identify optimal control gains at the Nash equilibrium, minimizing a predefined performance cost. The effectiveness, robustness, and practical applicability of the approach are validated through both numerical simulations and physical experiments, demonstrating its potential for real-world TCR formation operations.
{"title":"Optimizing bioinspired neurodynamic formation control for traffic cone robots under control input constraints: A noncooperative game approach","authors":"Jiale Zhang , Dongsheng Zhang , Zhiyong Li , Shengjie Jiao , Chuanwei Zhang , Siyuan Chang , Meng Wei","doi":"10.1016/j.jfranklin.2025.108383","DOIUrl":"10.1016/j.jfranklin.2025.108383","url":null,"abstract":"<div><div>This study presents an optimized bioinspired neurodynamic control framework for the formation placement and recovery control of traffic cone robots (TCRs) under constrained control inputs. A dynamic error model is constructed based on positional states, upon which a backstepping controller is designed and integrated with a bioinspired neurodynamic module to mitigate infeasible control commands arising from large initial deviations, ensuring actuator feasibility. Lyapunov-based analysis demonstrates closed-loop stability and guarantees the asymptotic convergence of formation errors. In addition, a multi-parameter optimization framework grounded in noncooperative game theory is proposed to identify optimal control gains at the Nash equilibrium, minimizing a predefined performance cost. The effectiveness, robustness, and practical applicability of the approach are validated through both numerical simulations and physical experiments, demonstrating its potential for real-world TCR formation operations.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108383"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-05DOI: 10.1016/j.jfranklin.2025.108384
Sadek Belamfedel Alaoui , Adnane Saoud , Abdelaziz Hmamed , Alejandro J. Rojas , El Houssaine Tissir
In this work, we extend the previously established scaled small gain problem to the realm of two-dimensional systems and introduce a new method to assess the stability of two-dimensional systems with time-varying delay. The method approximates the delayed state, in the horizontal and vertical directions, to constant delay states plus an approximation error. Using this transformation, the resulting model is expressed as an interconnection of two subsystems. The analysis based on the scaled small gain theorem and the Lyapunov’s method leads us to express the robust stability conditions in terms of a linear matrix inequality. Additionally, we introduce a new Lyapunov-Krasovskii functional, constructed using Legendre polynomials in two-dimensional space. Finally, we provide examples to demonstrate the effectiveness of our proposed method.
{"title":"Small-gain theorem-based stability analysis of two-dimensional systems with time delays","authors":"Sadek Belamfedel Alaoui , Adnane Saoud , Abdelaziz Hmamed , Alejandro J. Rojas , El Houssaine Tissir","doi":"10.1016/j.jfranklin.2025.108384","DOIUrl":"10.1016/j.jfranklin.2025.108384","url":null,"abstract":"<div><div>In this work, we extend the previously established scaled small gain problem to the realm of two-dimensional systems and introduce a new method to assess the stability of two-dimensional systems with time-varying delay. The method approximates the delayed state, in the horizontal and vertical directions, to constant delay states plus an approximation error. Using this transformation, the resulting model is expressed as an interconnection of two subsystems. The analysis based on the scaled small gain theorem and the Lyapunov’s method leads us to express the robust stability conditions in terms of a linear matrix inequality. Additionally, we introduce a new Lyapunov-Krasovskii functional, constructed using Legendre polynomials in two-dimensional space. Finally, we provide examples to demonstrate the effectiveness of our proposed method.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108384"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1016/j.jfranklin.2026.108402
Jianfeng Guo , Wei Qian , Wudi Li
This paper addresses the problem of event-triggered containment control for linear multi-agent systems. Initially, a state observer is designed to estimate the unmeasurable states of follower agents. Subsequently, a novel sampled-data-based hybrid error-driven adaptive dynamic event-triggered mechanism is proposed utilizing the periodically sampled observed states. This mechanism integrates state measurement errors, containment control errors, along with containment measurement errors, and employs dynamic auxiliary variables as well as adaptive threshold parameters that dynamically adjust in real time to meet the system’s performance requirements. By leveraging the observed states at triggering instants, a containment control protocol is further developed. Furthermore, a composite closed-loop error system, which includes containment errors, measurement errors, and observation errors, is constructed through model transformation. Consequently, the containment control problem is equivalently reformulated as an asymptotic stability analysis for a time-delayed error system. Sufficient conditions for containment control are derived from a stability analysis of the error system driven by the Lyapunov functional approach. A co-design method for controller gain, observer gain, and event-triggered parameters is then developed to ensure system performance. Finally, simulation results from two illustrative examples validate the effectiveness and superiority of the proposed event-triggered mechanism and containment control protocol.
{"title":"Improved sampled-data-based adaptive dynamic event-triggered containment control of multi-agent systems","authors":"Jianfeng Guo , Wei Qian , Wudi Li","doi":"10.1016/j.jfranklin.2026.108402","DOIUrl":"10.1016/j.jfranklin.2026.108402","url":null,"abstract":"<div><div>This paper addresses the problem of event-triggered containment control for linear multi-agent systems. Initially, a state observer is designed to estimate the unmeasurable states of follower agents. Subsequently, a novel sampled-data-based hybrid error-driven adaptive dynamic event-triggered mechanism is proposed utilizing the periodically sampled observed states. This mechanism integrates state measurement errors, containment control errors, along with containment measurement errors, and employs dynamic auxiliary variables as well as adaptive threshold parameters that dynamically adjust in real time to meet the system’s performance requirements. By leveraging the observed states at triggering instants, a containment control protocol is further developed. Furthermore, a composite closed-loop error system, which includes containment errors, measurement errors, and observation errors, is constructed through model transformation. Consequently, the containment control problem is equivalently reformulated as an asymptotic stability analysis for a time-delayed error system. Sufficient conditions for containment control are derived from a stability analysis of the error system driven by the Lyapunov functional approach. A co-design method for controller gain, observer gain, and event-triggered parameters is then developed to ensure system performance. Finally, simulation results from two illustrative examples validate the effectiveness and superiority of the proposed event-triggered mechanism and containment control protocol.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108402"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-03DOI: 10.1016/j.jfranklin.2025.108285
Simeng Song , Zhilin Liu , Shouzheng Yuan , Yingkai Ma , Lin Yang , Zhongxin Wang
In this paper, the problem of user-prescribed-time path-following control of the underactuated unmanned surface vessel is reported. We consider practical problems such as input saturation, external disturbances, model uncertainty, and unmeasurable velocity. First, we utilize a Gaussian error function to linearize the input saturation constraint. Further, we innovatively propose a set of switching user-prescribed-time extended state observers to accurately estimate the unmeasurable velocity and lumped disturbances in a user-prescribed time. Then, for the first time, we propose user-prescribed-time line-of-sight guidance to ensure that the position error converges in a user-prescribed time. Next, surge and heading controllers are constructed to achieve user-prescribed-time stabilization of the dynamic error. Finally, several commonly used schemes are presented as comparative cases to verify the superiority and feasibility of the proposed scheme at the simulation level.
{"title":"User-prescribed-time path-following control of underactuated unmanned surface vessels with switching extended state observers","authors":"Simeng Song , Zhilin Liu , Shouzheng Yuan , Yingkai Ma , Lin Yang , Zhongxin Wang","doi":"10.1016/j.jfranklin.2025.108285","DOIUrl":"10.1016/j.jfranklin.2025.108285","url":null,"abstract":"<div><div>In this paper, the problem of user-prescribed-time path-following control of the underactuated unmanned surface vessel is reported. We consider practical problems such as input saturation, external disturbances, model uncertainty, and unmeasurable velocity. First, we utilize a Gaussian error function to linearize the input saturation constraint. Further, we innovatively propose a set of switching user-prescribed-time extended state observers to accurately estimate the unmeasurable velocity and lumped disturbances in a user-prescribed time. Then, for the first time, we propose user-prescribed-time line-of-sight guidance to ensure that the position error converges in a user-prescribed time. Next, surge and heading controllers are constructed to achieve user-prescribed-time stabilization of the dynamic error. Finally, several commonly used schemes are presented as comparative cases to verify the superiority and feasibility of the proposed scheme at the simulation level.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108285"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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