Journal of The Franklin Institute-engineering and Applied Mathematics最新文献

{"title":"A uniform momentum-based distributed stochastic gradient tracking algorithm for non-convex optimization","authors":"Yantao Li ,&nbsp;Chaoxu Wu ,&nbsp;Yingjue Chen ,&nbsp;Keke Zhang ,&nbsp;Qingguo Lü ,&nbsp;Shaojiang Deng ,&nbsp;Huaqing Li","doi":"10.1016/j.jfranklin.2025.108040","DOIUrl":"10.1016/j.jfranklin.2025.108040","url":null,"abstract":"<div><div>This paper investigates distributed non-convex optimization problems, specifically focusing on a collaborative approach to optimize a global non-convex objective function across agents over networks. Problems of this nature along with consideration of efficiency usually emerge in a number of applications in artificial intelligence and engineering, mostly evident in machine learning, resource management, etc. To this end, we propose a novel distributed stochastic momentum acceleration algorithm which providing a unified momentum acceleration paradigm for distributed stochastic gradient tracking methods. By adjusting the parameters of the proposed algorithm, different distributed momentum acceleration methods can be obtained. In theoretical analysis, we prove that the proposed algorithm is capable of converging to a neighbourhood of a first-order stationary point of the non-convex function with a sub-linear convergence rate. Moreover, the proposed algorithm is proved to achieve convergence independent of network topology under certain conditions. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108040"},"PeriodicalIF":4.2,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057417","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}

{"title":"Adaptive tracking control of fractional-order nonlinear constrained systems with dead-zone","authors":"Fa Chen ,&nbsp;Lu Chen ,&nbsp;Huiyuan Li ,&nbsp;Jian-An Fang","doi":"10.1016/j.jfranklin.2025.108035","DOIUrl":"10.1016/j.jfranklin.2025.108035","url":null,"abstract":"<div><div>In this paper, the finite-time interval output constraints control problem is explored for fractional-order nonlinear systems (FONSs) with dead-zone. The so-called finite-time interval output constraints represent a type of output constraints that take place at the initial moment of the system operation and then end at a certain time. Unfortunately, the commonly used control methods based on the barrier Lyapunov function (BLF) fail to be directly utilized since the finite-time interval output constraints have an unconstrained phase. Moreover, the dead-zone nonlinearity contributes a further level of complexity and challenge to the tracking control issue. Therefore, by designing a modified error-dependent function and a novel time-varying scale function, we propose an improved adaptive tracking control technique, which not only counteracts the effects of dead-zone nonlinearity, but also handles finite-time interval output constraints, no constraints, and infinite-time output constraints problem (i.e., output constraints are always present) without modifying the control structure. Finally, simulations verify the effectiveness of the stated control strategy.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108035"},"PeriodicalIF":4.2,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145045055","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}

{"title":"Robust and imperceptible medical image watermarking for telemedicine applications based on transform-domain and neural clustering techniques","authors":"Ahmed Saïd Beggari ,&nbsp;Ali Wali ,&nbsp;Amine Khaldi ,&nbsp;Med Redouane Kafi ,&nbsp;Sahu Aditya Kumar","doi":"10.1016/j.jfranklin.2025.108039","DOIUrl":"10.1016/j.jfranklin.2025.108039","url":null,"abstract":"<div><div>In telemedicine, the protection of exchanged medical data, particularly images, is essential to guarantee the confidentiality and integrity of sensitive information. The aim of this work is to develop a watermarking method that ensures the security of these data while preserving their visual quality. We propose a two-stage approach, in the first step, a text watermark containing sensitive information is embedded in a grayscale image using a combination of the Discrete Cosine Transform (DCT) and the K-means algorithm. In the second step, this watermarked image is embedded in a color medical image using the Discrete Wavelet Transform (DWT) and the Self-Organizing Map (SOM) algorithm, with Reed-Solomon (RS) coding to enhance security. Experimental results show that our method achieves high imperceptibility, with a peak signal-to-noise ratio (PSNR) of 45 dB. In terms of robustness, our approach effectively resists various attacks, displaying a normalized cross correlation coefficient (NCC) close to 1 for several types of attack. Statistically, our method achieves a 5-10 % higher PSNR compared to state-of-the-art techniques and maintains an NCC above 0.99 under noise, compression, and filtering attacks, outperforming existing methods by 8–15 % in robustness metrics.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108039"},"PeriodicalIF":4.2,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019839","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}

{"title":"3D point stabilization control of AUVs based on RDNN-ADP with uncertainty boundary information unknown","authors":"Puxin Chai ,&nbsp;Yushan Sun ,&nbsp;Wenhua Wu ,&nbsp;Houcun Zhou ,&nbsp;Zhaolin Fan","doi":"10.1016/j.jfranklin.2025.107961","DOIUrl":"10.1016/j.jfranklin.2025.107961","url":null,"abstract":"<div><div>This study propose a robust dual neural network adaptive dynamics programming (RDNN-ADP) control scheme to address the three-dimensional point stabilization problem of AUV when the bounds of system uncertainty are unknown or difficult to determine precisely. The control laws are systematically designed using an integrated approach that combines the backstepping technique and optimal control theory. The optimal virtual reference is approximated by solving the kinematic HJB equation using a neural network (NN) which is used as the reference signal to design the dynamics controller. The optimal control input is obtained by approximating the dynamics HJB equation using NN. The weight update law of NN is derived using the gradient descent method. During the controller design phase, the conventional Actor-Critic (AC) architecture of the ADP framework is systematically simplified through structural optimization, enhancing computational efficiency while maintaining control performance. To improve robustness, an adaptive compensation mechanism is incorporated into the control architecture. This design enables the controller to maintain stable performance despite system uncertainties. To evaluate the performance of the proposed method, extensive comparative simulations are conducted using two benchmark approaches: the conventional ADP method based on the AC framework and the differential dynamics programming (DDP) method. Simulation results demonstrate that the proposed method exhibits superior performance in terms of accuracy and convergence rate. Furthermore, to validate the robustness enhancement provided by the uncertainty compensation mechanism, additional comparative studies were conducted using the uncompensated control system. The experimental results revealed that the proposed compensation scheme significantly improved the system's robustness against uncertainties, even in the absence of prior knowledge about uncertainty bounds. It outperformed the uncompensated counterpart in disturbance rejection capability and stability maintenance.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 107961"},"PeriodicalIF":4.2,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145026953","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}

{"title":"Design and stability analysis of impulsive control fractional neural network models in industrial products emotion recognition","authors":"Trayan Stamov","doi":"10.1016/j.jfranklin.2025.108029","DOIUrl":"10.1016/j.jfranklin.2025.108029","url":null,"abstract":"<div><div>This article proposes a design of fractional discrete impulsive neural networks that can be applied to the recognition of emotions generated by industrial products. Neural network systems are currently used in various applications from fields such as computer science, engineering, economics or medicine to increase the accuracy of detection, recognition and optimization. The suggested new neural network approach for learning and classifying emotional expressions elicited by industrial products, extends and generalizes the existing integer-order neural network approaches proposed in the literature. Furthermore, a hybrid stability notion is introduced, and the corresponding stability analysis is proposed which is essential for the practical design and applications of the considered neural network model. Using the impulsive control approach and the Lyapunov function technique, criteria for the practical stability of the model’s nodes have been established. The fact that the impulsive control has shown great potential in recent years increases the capabilities and computational efficiency of the introduced strategy. Additionally, examples and discussion are presented to exhibit the validity of the proposed results.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108029"},"PeriodicalIF":4.2,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019841","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}

{"title":"Finite-time stochastic time-varying optimal control for high-speed train under Wiener and Poisson stochastic fluctuations","authors":"Xiaomin Zhou ,&nbsp;Min Zhou ,&nbsp;Aming Li ,&nbsp;Hairong Dong","doi":"10.1016/j.jfranklin.2025.108032","DOIUrl":"10.1016/j.jfranklin.2025.108032","url":null,"abstract":"<div><div>High-speed train (HST) is often impacted by random disturbances such as voltage fluctuations, severe weather, and random measurement signals, potentially leading to security risks and energy waste. This paper investigates time-varying stochastic finite-time optimal guaranteed cost control (TSFOC) for the HST velocity tracking problem under unknown stochastic disturbances based on the finite time control method, optimal control method, and stochastic system theory. Utilizing the Itô-Levy formula and time-varying quadratic Lyapunov function, the velocity tracking controller design problem of the HST is transformed into a differential linear matrix inequalities (DLMIs) optimization problem. This problem requires us to design a state feedback controller with time-varying gains, ensuring that the error remains bounded and minimized within a finite time, while also achieving optimal energy efficiency. Moreover, a time-varying parameter algorithm is given to solve the DLMIs optimization problem. Finally, the effectiveness of the proposed method is demonstrated through simulation cases under two different initial operating conditions and temporary speed-limiting scenarios. Simulation results show that the TSFOC method outperforms the PID control and guaranteed cost control method, with better speed tracking performance, energy saving, transient performance, robustness, and anti-interference performance.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108032"},"PeriodicalIF":4.2,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019840","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}

{"title":"Adaptive asynchronous control of sojourn-probability-based fuzzy systems with aperiodic sampling and DoS attacks","authors":"Yue Huang ,&nbsp;Shoucheng Yuan ,&nbsp;Jun Cheng ,&nbsp;Hailing Wang ,&nbsp;Yonghong Chen","doi":"10.1016/j.jfranklin.2025.108031","DOIUrl":"10.1016/j.jfranklin.2025.108031","url":null,"abstract":"<div><div>This paper addresses the problem of output feedback control for nonlinear Takagi-Sugeno (T-S) fuzzy systems subject to stochastic aperiodic sampling and Denial-of-Service (DoS) attacks. Unlike conventional approaches that rely on periodic sampling and assume full knowledge of Markov transition probabilities, this work introduces a flexible control framework based on sojourn probabilities, which are more readily accessible in practical scenarios. With respect to the fact that both the stochastic sampling mechanism and unpredictable DoS attack occurrences, the proposed method explicitly accounts for dual randomness and further incorporates a novel dynamic mismatch model to capture asynchronous phenomena between the system and controller modes. The controller is synthesized to ensure stochastic stability and to achieve a prescribed performance index, even under communication uncertainties and cyber-attacks. Theoretical results are rigorously established via Lyapunov-based analysis and linear matrix inequalities. Comprehensive simulation studies using a benchmark nonlinear robot arm system demonstrate the validity of the proposed strategy.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108031"},"PeriodicalIF":4.2,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019838","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}

{"title":"Fault detection filtering for uncertain Markov jump systems with DoS attacks under weighted try-once-discard protocol","authors":"Tongtong Ding ,&nbsp;Cheng Tan ,&nbsp;Lili Li ,&nbsp;Xiangyong Chen","doi":"10.1016/j.jfranklin.2025.108008","DOIUrl":"10.1016/j.jfranklin.2025.108008","url":null,"abstract":"<div><div>This paper addresses the fault detection (FD) problem for uncertain Markov jump systems (MJSs) operating under the weighted try-once-discard (WTOD) protocol and vulnerable to denial-of-service (DoS) attacks. Specifically, the WTOD protocol optimizes communication efficiency by determining whether sensor nodes should proceed with transmission. However, DoS attacks disrupt data transmission between sensors and the zero-order holder (ZOH), and the system matrices of the considered Markov jump systems contain parametric uncertainties. Our main objective is to design a FD filter for the aforementioned system that accounts for DoS attacks while utilizing the WTOD protocol. We establish sufficient conditions for the asymptotic stability and prescribed <span><math><msub><mi>H</mi><mi>∞</mi></msub></math></span> performance of the residual system. Furthermore, utilizing solutions to a set of linear matrix inequalities (LMIs), we derive the desired parameters for the FD filter. Finally, simulations are conducted to demonstrate the feasibility and effectiveness of the proposed FD filtering approach.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108008"},"PeriodicalIF":4.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989223","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}

{"title":"Hierarchical dynamic graphical games for optimal leader-follower consensus control","authors":"Jia Long ,&nbsp;Tao Xu ,&nbsp;Dengxiu Yu ,&nbsp;C.L. Philip Chen","doi":"10.1016/j.jfranklin.2025.108015","DOIUrl":"10.1016/j.jfranklin.2025.108015","url":null,"abstract":"<div><div>In this paper, a hierarchical dynamic graphical game (HDGG) model is proposed to extend the existing optimal leader-follower consensus control framework for a class of linear stochastic systems. Owing to the interaction relationships and communication constraints among agents determined by the communication topology, the multi-agent system naturally exhibits a multi-stage hierarchical decision-making mechanism that relies solely on the local perceptions available to each agent. The proposed model introduces a multi-layer distributed structure through sequential decision-making, which accounts for both in-degree and out-degree tracking errors in a generalized leader-follower sense. Following the bottom-up principle, hierarchical and simultaneous optimal control policies for each agent are derived from the bottom to the top in a dynamic stochastic environment. A corresponding policy gradient algorithm is developed for the implementation of HDGG under both known and unknown parameter settings, and its convergence and optimality are guaranteed under certain conditions. Furthermore, the control policies are shown to constitute a Stackelberg-Nash equilibrium owing to the unique solution of the corresponding Riccati equation. Finally, an illustrative example is provided to demonstrate the efficacy of the proposed algorithm in both model-based and model-free settings.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108015"},"PeriodicalIF":4.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004427","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}

{"title":"Event-triggered observer-based dynamic positioning control of unmanned marine vehicle systems under deception attack","authors":"Haibin Sun ,&nbsp;Xiaoliang Liu ,&nbsp;Linlin Hou","doi":"10.1016/j.jfranklin.2025.108002","DOIUrl":"10.1016/j.jfranklin.2025.108002","url":null,"abstract":"<div><div>This study investigates dynamic positioning event-triggered control for unmanned marine vehicles in the presence of random deception attacks and ocean disturbances. First, an event-triggered mechanism is developed within the sensor channel to optimize system resource utilization. Unlike traditional dynamic ETMs, this study introduces a novel dynamic memory event-triggered mechanism. Second, the triggered signals are used to construct a proper state observer. Based on the state observer’s output, a disturbance observer is designed to estimate unknown disturbances. Then, a suitable observer based controller is designed. Moreover, the mean-square asymptotic stability of the closed-loop system is established using Lyapunov theory. Finally, the effectiveness of the proposed control scheme is validated through simulation on a UMV system.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 15","pages":"Article 108002"},"PeriodicalIF":4.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145045053","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}