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

{"title":"Robust blade pitch control of semi-submersible floating offshore wind turbines based on the modified super-twisting sliding-mode algorithm","authors":"","doi":"10.1016/j.jfranklin.2024.107279","DOIUrl":"10.1016/j.jfranklin.2024.107279","url":null,"abstract":"<div><div>In this paper, a novel robust collective blade pitch controller (CBPC) is proposed for the semi-submersible floating offshore wind turbine (FOWT) above the rated wind speed. The proposed CBPC is based on the modified super-twisting sliding-mode (MSTSM) algorithm. Firstly, based on a control-oriented model of the semi-submersible FOWT, the dynamics of the rotor speed and the platform pitch rate considering the lumped disturbances, which consist of external disturbances, parametric uncertainties and unmodeled dynamics, are derived. Afterward, the MSTSM algorithm-based CBPC (MSTSM-CBPC) is designed for regulating the generator power to its rated value and reducing the platform pitching motion. Comparative co-simulation tests among the gain-scheduling proportional-integral CBPC, the standard STSM algorithm-based CBPC and the proposed MSTSM-CBPC are performed. Simulation results validate the effectiveness and the superiority of the proposed MSTSM-CBPC.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322460","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":"Distributed time-varying optimization with prescribed-time approach","authors":"","doi":"10.1016/j.jfranklin.2024.107270","DOIUrl":"10.1016/j.jfranklin.2024.107270","url":null,"abstract":"<div><p>This work focuses on distributed time-varying optimization algorithms that can converge in a prescribed time period, both single-integrator systems and double-integrator systems are considered. A nested structure is proposed for applying prescribed-time approach to distributed time-varying optimization problems in this work. For single-integrator systems, the prescribed time interval is divided into three sub-intervals, then the average consensus estimation, the state consensus, and the optimized trajectory tracking are achieved sequentially through the time-scale function in the three sub-time intervals. This nested structure and the properties of the time-scale function ensure that the first-order algorithm is continuous and bounded. Therefore, the algorithm can be extended to double integrator systems by tracking the virtual first-order input signal. The validity of the proposed first-order and second-order algorithms is verified through optimal dynamic trajectory tracking experiments for indoor UAV clusters.</p></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271613","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 control of bilateral teleoperators with convergent parameter estimation and guaranteed compliance","authors":"","doi":"10.1016/j.jfranklin.2024.107291","DOIUrl":"10.1016/j.jfranklin.2024.107291","url":null,"abstract":"<div><div>Although adaptive control has been studied for teleoperation systems in the past decades, the convergence of parameter estimation is generally difficult to claim in the existing methods, and thus only specific scenarios (e.g., free motion) and partial operation performance (e.g., synchronization) have been addressed. In this paper, we found that the convergence of parameter estimation is crucial for bilateral teleoperation systems to retain the guaranteed operation performances, including compliance in the tracking motion and transparency in the contact motion. Accordingly, this paper suggests an alternative adaptive control for bilateral teleoperation systems, where a new adaptive law with the estimation errors as leakage terms is developed to obtain finite-time convergence of the parameter estimation. This convergent property allows to compensate for the undesired dynamics (e.g., gravity) in the closed-loop system so as to achieve ideal compliance and transparency. The control system’s stability and performances under constant time delays are analyzed for three scenarios: free motion, tracking motion, and contact motion. The quantitative relationship between the joint velocities and the human torques in the tracking motion is also studied, and the transparency is addressed in the contact motion. Simulations and experiments on a Baxter robot all showcase the effectiveness and superiority of the developed approach.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316213","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":"New conditions for stabilization and l2-gain analysis of discrete-time switched systems","authors":"","doi":"10.1016/j.jfranklin.2024.107207","DOIUrl":"10.1016/j.jfranklin.2024.107207","url":null,"abstract":"<div><p>This paper uses a time-varying state feedback control method to investigate the global asymptotic stabilization issue of discrete-time switched systems with dwell-time constraints. A discrete dwell-time partitioning technique is proposed to design a time-varying Lyapunov function, which has a distinct characteristic that its value decreases at any time, even at each switching instant. Applying the partitioning technique and the time-varying control method, some new conditions with adjustable computational complexity are derived for stabilizing the discrete-time switched systems. Moreover, the extension to <span><math><msub><mrow><mi>l</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-gain computation is presented in the sequel. Four examples are provided to illustrate the merits of the theoretical analysis.</p></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271609","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":"Class incremental learning with analytic learning for hyperspectral image classification","authors":"","doi":"10.1016/j.jfranklin.2024.107285","DOIUrl":"10.1016/j.jfranklin.2024.107285","url":null,"abstract":"<div><div>Hyperspectral image classification (HSIC) is crucial for applications in agriculture and environmental monitoring. As ground objects evolve and remote sensing technology progresses, there is a growing need for HSIC models that can adapt to new data classes without requiring to be retrained from scratch. Throughout the continual learning procedure, the model is expected to not only effectively extract spatial–spectral features from the hyperspectral image but also alleviate the issue of catastrophic forgetting, i.e., the model forgets the learned classes’ knowledge when accessing novel classes during the training process. In this paper, for the HSIC task, we propose a class incremental learning method (HSI-CIL) that is based on analytic learning, a technique that converts network training into linear problems. Specifically, The HSI-CIL model consists of a lightweight feature extractor, a Feature Processing Module (FPM) and an Analytic Linear Classifier (ALC). This model does not need data storage for old and new classes and has only one epoch in the incremental learning stage, so it has lower consumption of resources and training time than several attempts have been proposed for addressing catastrophic forgetting. We perform abundant experiments with the proposed HSI-CIL on three publicly available hyperspectral datasets including Indian Pines, Pavia University, and Salinas. The experiments demonstrate that our HSI-CIL exceeds the state-of-the-art class incremental learning (CIL) techniques applied in HSIC with a certain gap.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322461","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 adaptive control based on output feedback and auxiliary variables for time-varying parameters and disturbances","authors":"","doi":"10.1016/j.jfranklin.2024.107273","DOIUrl":"10.1016/j.jfranklin.2024.107273","url":null,"abstract":"<div><div>This paper presents a finite-time adaptive control scheme tailored for a diverse range of unknown discrete-time systems, with a specific emphasis on BLDC motor position control. The approach leverages an auxiliary variable within an output feedback framework, adeptly circumventing the causality problem without necessitating the use of state or disturbance observers. Through the application of finite-time convergence techniques, the control law demonstrates robust performance even in the presence of time-varying parameters and compact disturbances. Additionally, the proposed time-varying estimator, based on multi-input fuzzy emulated network (MiFREN), offers a practical solution for handling unknown dynamics and disturbances, making it well-suited for real-world applications where accurate mathematical models may be unavailable. Extensive experimental validation is conducted to evaluate the efficacy of the proposed scheme, including comparisons with existing controllers. The results highlight the superiority of the approach, particularly in terms of tracking accuracy and robustness against disturbances.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316209","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":"Projected gradient descent method for cardinality-constrained portfolio optimization","authors":"","doi":"10.1016/j.jfranklin.2024.107267","DOIUrl":"10.1016/j.jfranklin.2024.107267","url":null,"abstract":"<div><div>Cardinality-constrained portfolio optimization aims at determining the investment weights on given assets using the historical data. This problem typically requires three constraints, namely, capital budget, long–only, and sparsity. The sparsity restraint allows investment managers to select a small number of stocks from the given assets. Most existing approaches exploit the penalty technique to handle the sparsity constraint. Therefore, they require tweaking the associated regularization parameter to obtain the desired cardinality level, which is time-consuming. This paper formulates the sparse portfolio design as a cardinality-constrained nonconvex optimization problem, where the sparsity constraint is modeled as a bounded <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-norm. The projected gradient descent (PGD) method is then utilized to deal with the resultant problem. Different from existing algorithms, the suggested approach, called <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PGD, can explicitly control the cardinality level. In addition, its convergence is established. Specifically, the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PGD guarantees that the objective function value converges, and the variable sequences converges to a local minimum. To remedy the weaknesses of gradient descent, the momentum technique is exploited to enhance the performance of the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PGD, yielding <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PMGD. Numerical results on four real-world datasets, viz. NASDAQ 100, S&amp;P 500, Russell 1000, and Russell 2000 exhibit the superiority of the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PGD and <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-PMGD over existing algorithms in terms of mean return and Sharpe ratio.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328211","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":"H∞ security control for 2-D switched time delay systems under arbitrary delay time-variation rate and stochastic cyber attacks","authors":"","doi":"10.1016/j.jfranklin.2024.107290","DOIUrl":"10.1016/j.jfranklin.2024.107290","url":null,"abstract":"<div><p>This study focuses on <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> security control for 2-D switched time delay systems subject to stochastic cyber attacks by the Roesser model, where the delay time-variation rate can be arbitrary. First, the time-delay system is modeled as the feedback interconnection of the delay-less system. To guarantee the security of the system under stochastic cyber attacks, a state-dependent switching signal and an anti-deception attack controller are constructed. Stability conditions of 2-D delay-less feedback interconnection systems are given for the first time. Then, for the considered system, some criteria based on bilinear matrix inequalities (BMIs) are established via the Lyapunov function technology such that the mean-square asymptotic stability with <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance is guaranteed under arbitrary delay time-variation rate. Moreover, a cone-complement linearization (CCL) method is proposed to compute the optimized controller gains for BMIs. The effectiveness of the proposed method is validated via two numerical simulations.</p></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271611","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":"Bumpless transfer control for switched time-delay systems with application to aero-engine control","authors":"","doi":"10.1016/j.jfranklin.2024.107289","DOIUrl":"10.1016/j.jfranklin.2024.107289","url":null,"abstract":"<div><div>For switched time-delay systems, the bumpless transfer control issue is investigated by utilizing the multiple piecewise Lyapunov–Krasovskii function approach. First, a time-delay-dependent bumpless transfer concept is put forward to depict the transient performance of switched time-delay systems, which restricts the bumps in the amplitude of the present state and the time-delay state, simultaneously. Second, a state-dependent switching signal with a prescribed time is designed to avoid switching frequently. A time-varying switching controller is developed to decrease control bumps. Third, under the premise of achieving asymptotic stability, a solvability condition ensuring a satisfactory bumpless transfer performance is derived through relaxing the traditional bumpless transfer condition. Finally, an instance of the aero-engine control system is used for exhibiting the validity of the presented method.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328213","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":"Blind non-linear spectral unmixing with spatial coherence for hyper and multispectral images","authors":"","doi":"10.1016/j.jfranklin.2024.107282","DOIUrl":"10.1016/j.jfranklin.2024.107282","url":null,"abstract":"<div><p>Multi and hyperspectral images have become invaluable sources of information, revolutionizing various fields such as remote sensing, environmental monitoring, agriculture and medicine. In this expansive domain, the multi-linear mixing model (MMM) is a versatile tool to analyze spatial and spectral domains by effectively bridging the gap between linear and non-linear interactions of light and matter. This paper introduces an upgraded methodology that integrates the versatility of MMM in non-linear spectral unmixing, while leveraging spatial coherence (SC) enhancement through total variation theory to mitigate noise effects in the abundance maps. Referred to as non-linear extended blind end-member and abundance extraction with SC (NEBEAE-SC), the proposed methodology relies on constrained quadratic optimization, cyclic coordinate descent algorithm, and the split Bregman formulation. The validation of NEBEAE-SC involved rigorous testing on various hyperspectral datasets, including a synthetic image, remote sensing scenarios, and two biomedical applications. Specifically, our biomedical applications are focused on classification tasks, the first addressing hyperspectral images of in-vivo brain tissue, and the second involving multispectral images of ex-vivo human placenta. Our results demonstrate an improvement in the abundance estimation by NEBEAE-SC compared to similar algorithms in the state-of-the-art by offering a robust tool for non-linear spectral unmixing in diverse application domains.</p></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271614","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}