Pub Date : 2024-11-16DOI: 10.1016/j.jfranklin.2024.107404
Zhen Su , Jürgen Kurths , Henning Meyerhenke
Network (or graph) sparsification benefits downstream graph mining tasks. Finding a sparsified subgraph similar to the original graph is, however, challenging due to the requirement of preserving various (or at least representative) network properties. In this paper, we propose a general hybrid edge sampling scheme named LOGA, as the combination of the Local-filtering-based Random Edge sampling (LRE) (Hamann et al., 2016) and the Game-theoretic Sparsification with Tolerance (GST) (Su et al., 2022). LOGA fully utilizes the advantages of GST — in preserving complex structural properties by preserving local node properties in expectation – and LRE – in preserving the connectivity of a given network. Specifically, we first prove the existence of multiple equilibria in GST. This insight leads us to propose LOGA and its variant LOGA by refining GST. LOGA is obtained by regarding LRE as an empirically good initializer for GST, while LOGA is obtained by further including a constrained update for GST. In this way, LOGA/LOGA generalize the work on GST to graphs with weights and different densities, without increasing the asymptotic time complexity. Extensive experiments on 26 weighted and unweighted networks with different densities demonstrate that LOGA performs best for all 26 instances, i.e., they preserve representative network properties better than state-of-the-art sampling methods alone.
{"title":"Generic network sparsification via hybrid edge sampling","authors":"Zhen Su , Jürgen Kurths , Henning Meyerhenke","doi":"10.1016/j.jfranklin.2024.107404","DOIUrl":"10.1016/j.jfranklin.2024.107404","url":null,"abstract":"<div><div>Network (or graph) sparsification benefits downstream graph mining tasks. Finding a sparsified subgraph <span><math><mover><mrow><mi>G</mi></mrow><mrow><mo>ˆ</mo></mrow></mover></math></span> similar to the original graph <span><math><mi>G</mi></math></span> is, however, challenging due to the requirement of preserving various (or at least representative) network properties. In this paper, we propose a general hybrid edge sampling scheme named LOGA, as the combination of the <u>Lo</u>cal-filtering-based Random Edge sampling (LRE) (Hamann et al., 2016) and the <u>Ga</u>me-theoretic Sparsification with Tolerance (GST) (Su et al., 2022). LOGA fully utilizes the advantages of GST — in preserving complex structural properties by preserving local node properties in expectation – and LRE – in preserving the connectivity of a given network. Specifically, we first prove the existence of multiple equilibria in GST. This insight leads us to propose LOGA and its variant LOGA<span><math><msup><mrow></mrow><mrow><mi>s</mi><mi>c</mi></mrow></msup></math></span> by refining GST. LOGA is obtained by regarding LRE as an empirically good initializer for GST, while LOGA<span><math><msup><mrow></mrow><mrow><mi>s</mi><mi>c</mi></mrow></msup></math></span> is obtained by further including a constrained update for GST. In this way, LOGA/LOGA<span><math><msup><mrow></mrow><mrow><mi>s</mi><mi>c</mi></mrow></msup></math></span> generalize the work on GST to graphs with weights and different densities, without increasing the asymptotic time complexity. Extensive experiments on 26 weighted and unweighted networks with different densities demonstrate that LOGA<span><math><msup><mrow></mrow><mrow><mi>s</mi><mi>c</mi></mrow></msup></math></span> performs best for all 26 instances, i.e., they preserve representative network properties better than state-of-the-art sampling methods alone.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107404"},"PeriodicalIF":3.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-14DOI: 10.1016/j.jfranklin.2024.107394
Liang Zhang , Jun Song , Shuping He
This paper investigates the finite-time estimation of the time-varying Geometrical Center of Targets (GCT) in Multi-Target Enclosing Control Problem (MTECP). Existing estimators exhibit a chattering phenomenon that is harmful to the mechanical components of the deployed robots when forming the enclosing formation. We thereby propose two chattering-free finite-time estimators, employing a fully distributed approach demanding only the local observation and neighboring communication. The first fractional-order estimator is formulated by replacing the discontinuous term in the existing finite-time estimator by a fractional-order term, which remains smooth when the consensus error approaches zero. Theoretical results show that the estimation error can be stabilized into a bounded region adjustable by tuning the parameters. Then, another novel estimator with double integral architecture is designed to further eliminate the bounded estimation error in the first-order estimator i.e. can achieve exact tracking of the GCT in finite-time. Its continuity of estimation arises from the integration of a discontinuous unit-vector term and three more internal states are introduced to realize the double integral architecture. Finally, simulation and comparison results validate the correctness and smoothness of the proposed estimators.
{"title":"Chattering-free and finite-time estimation of the time-varying geometrical center for the multi-targets enclosing control problem","authors":"Liang Zhang , Jun Song , Shuping He","doi":"10.1016/j.jfranklin.2024.107394","DOIUrl":"10.1016/j.jfranklin.2024.107394","url":null,"abstract":"<div><div>This paper investigates the finite-time estimation of the time-varying Geometrical Center of Targets (GCT) in Multi-Target Enclosing Control Problem (MTECP). Existing estimators exhibit a chattering phenomenon that is harmful to the mechanical components of the deployed robots when forming the enclosing formation. We thereby propose two chattering-free finite-time estimators, employing a fully distributed approach demanding only the local observation and neighboring communication. The first fractional-order estimator is formulated by replacing the discontinuous term in the existing finite-time estimator by a fractional-order term, which remains smooth when the consensus error approaches zero. Theoretical results show that the estimation error can be stabilized into a bounded region adjustable by tuning the parameters. Then, another novel estimator with double integral architecture is designed to further eliminate the bounded estimation error in the first-order estimator i.e. can achieve exact tracking of the GCT in finite-time. Its continuity of estimation arises from the integration of a discontinuous unit-vector term and three more internal states are introduced to realize the double integral architecture. Finally, simulation and comparison results validate the correctness and smoothness of the proposed estimators.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107394"},"PeriodicalIF":3.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703145","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 : 2024-11-14DOI: 10.1016/j.jfranklin.2024.107397
Liang Nie , Hui Wang , Yichong Sun
In this paper, a switched linear parameter-varying (LPV) resilient tracking controller is designed for rigid-body under actuator faults, uncertainties in measurement of scheduling parameters and time-delay in detection of system modes. The nonlinear attitude dynamics of rigid-body is constructed as a switched LPV system in which persistent dwell-time switching rule is used to regulate the switches caused by abrupt and intermittent actuator failures. Thereafter, by constructing a class of both parameter-dependent and time-dependent multiple Lyapunov functions (MLFs), a switched LPV resilient tracking controller is developed in order that the global uniform exponential stability and desired performance of the underlying system are achieved even with uncertain scheduling parameters, mismatched modes and persistent external disturbances. Furthermore, the nonconvex conditions of control synthesis are converted into parameterized linear matrix inequalities that can be readily resolved via gridding technique. Finally, the availability of the provided approach is evaluated with a numerical simulation.
{"title":"Switched LPV resilient tracking control for rigid-body with defective actuators and sensors","authors":"Liang Nie , Hui Wang , Yichong Sun","doi":"10.1016/j.jfranklin.2024.107397","DOIUrl":"10.1016/j.jfranklin.2024.107397","url":null,"abstract":"<div><div>In this paper, a switched linear parameter-varying (LPV) resilient tracking controller is designed for rigid-body under actuator faults, uncertainties in measurement of scheduling parameters and time-delay in detection of system modes. The nonlinear attitude dynamics of rigid-body is constructed as a switched LPV system in which persistent dwell-time switching rule is used to regulate the switches caused by abrupt and intermittent actuator failures. Thereafter, by constructing a class of both parameter-dependent and time-dependent multiple Lyapunov functions (MLFs), a switched LPV resilient tracking controller is developed in order that the global uniform exponential stability and desired <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance of the underlying system are achieved even with uncertain scheduling parameters, mismatched modes and persistent external disturbances. Furthermore, the nonconvex conditions of control synthesis are converted into parameterized linear matrix inequalities that can be readily resolved via gridding technique. Finally, the availability of the provided approach is evaluated with a numerical simulation.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107397"},"PeriodicalIF":3.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703144","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 : 2024-11-14DOI: 10.1016/j.jfranklin.2024.107393
Liang Liu
This paper focuses on the problem of adaptive state-feedback control for a class of stochastic high-order nonlinearly parameterized systems with stochastic integral input-to-state stable (SiISS) inverse dynamics. By employing the parameter separation principle and the tool of adding a power integrator, a one-dimensional adaptive state-feedback controller is constructed. On the basis of stochastic LaSalle theorem and SiISS small-gain type conditions, the proposed adaptive controller can guarantee that all signals of the closed-loop system are bounded almost surely and the stochastic closed-loop system is globally stable in probability. In addition, the aforementioned control scheme is generalized to some kinds of stochastic nonlinear systems with SiISS inverse dynamics, and some new control results are obtained. Two simulation examples are provided to verify the effectiveness of the adaptive controller.
{"title":"Adaptive control of stochastic high-order nonlinearly parameterized systems with SiISS inverse dynamics","authors":"Liang Liu","doi":"10.1016/j.jfranklin.2024.107393","DOIUrl":"10.1016/j.jfranklin.2024.107393","url":null,"abstract":"<div><div>This paper focuses on the problem of adaptive state-feedback control for a class of stochastic high-order nonlinearly parameterized systems with stochastic integral input-to-state stable (SiISS) inverse dynamics. By employing the parameter separation principle and the tool of adding a power integrator, a one-dimensional adaptive state-feedback controller is constructed. On the basis of stochastic LaSalle theorem and SiISS small-gain type conditions, the proposed adaptive controller can guarantee that all signals of the closed-loop system are bounded almost surely and the stochastic closed-loop system is globally stable in probability. In addition, the aforementioned control scheme is generalized to some kinds of stochastic nonlinear systems with SiISS inverse dynamics, and some new control results are obtained. Two simulation examples are provided to verify the effectiveness of the adaptive controller.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107393"},"PeriodicalIF":3.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703720","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 : 2024-11-13DOI: 10.1016/j.jfranklin.2024.107391
Hao Zhang , Zhenyu Li , Yongle Chen , Chenchen Lu , Pengfei Yan
The Radial Harmonic Fourier Moments(RHFMs) is a kind of continuous orthogonal moments with good performance of image representation and reconstruction. Most of existing methods focused on improving the computation of RHFMs, and ignored the research about the reconstruction. Therefore, a fast reconstruction method based on RHFMs by using inverse fast Fourier transform(IFFT) is proposed in this paper. The time cost of reconstruction is greatly decreased. Then, the fast computation method is extend to the quaternion radial harmonic Fourier moments(QRHFMs) by using quaternion theory, which is suitable for the color image representation. Finally, a color image watermarking scheme based on the QRHFMs is conducted. During the embedding process, considering the association between QRHFMs and quaternion discrete Fourier transform(QDFT), the watermark is embedded in the magnitude of QRHFMs symmetrically. The center area of cover image is ignored in order to improve the quality of watermarked image. Experiments denote that proposed watermarking algorithm has low computation complexity and good robust against geometric attacks and common attacks.
{"title":"Fast image reconstruction method using radial harmonic Fourier moments and its application in digital watermarking","authors":"Hao Zhang , Zhenyu Li , Yongle Chen , Chenchen Lu , Pengfei Yan","doi":"10.1016/j.jfranklin.2024.107391","DOIUrl":"10.1016/j.jfranklin.2024.107391","url":null,"abstract":"<div><div>The Radial Harmonic Fourier Moments(RHFMs) is a kind of continuous orthogonal moments with good performance of image representation and reconstruction. Most of existing methods focused on improving the computation of RHFMs, and ignored the research about the reconstruction. Therefore, a fast reconstruction method based on RHFMs by using inverse fast Fourier transform(IFFT) is proposed in this paper. The time cost of reconstruction is greatly decreased. Then, the fast computation method is extend to the quaternion radial harmonic Fourier moments(QRHFMs) by using quaternion theory, which is suitable for the color image representation. Finally, a color image watermarking scheme based on the QRHFMs is conducted. During the embedding process, considering the association between QRHFMs and quaternion discrete Fourier transform(QDFT), the watermark is embedded in the magnitude of QRHFMs symmetrically. The center area of cover image is ignored in order to improve the quality of watermarked image. Experiments denote that proposed watermarking algorithm has low computation complexity and good robust against geometric attacks and common attacks.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107391"},"PeriodicalIF":3.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662796","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 : 2024-11-13DOI: 10.1016/j.jfranklin.2024.107395
Qingxian Jia , Rui Shu , Dan Yu , Chengxi Zhang , Lining Tan
This article investigates neural network (NN)-based prescribed performance control with collision avoidance for spacecraft formation systems in the presence of space perturbations and thruster faults. First, an artificial potential function is constructed to maintain spacecraft within communication range and avoid collisions. A prescribed performance function is then employed to constrain position errors within a preset boundary. Furthermore, a learning non-singular terminal sliding mode control (LNTSMC) law is developed to ensure that both the steady-state and transient performance of position tracking errors meet the prescribed performance constraints. A novel learning NN model is incorporated to estimate and compensate for the synthesized perturbations, utilizing an iterative learning algorithm to update the weights of the NN, thereby reducing computational complexity. The proposed LNTSMC scheme effectively addresses issues of inter-spacecraft collision avoidance, prescribed dynamic and steady-state control performance, and robust fault tolerance without imposing additional constraints on thruster faults. A rigorous stability analysis is provided, and the effectiveness and applicability of the proposed method are validated through simulation comparisons.
本文研究了在存在空间扰动和推进器故障的情况下，基于神经网络（NN）的航天器编队系统避免碰撞的规定性能控制。首先，构建了一个人工势函数，以将航天器保持在通信范围内并避免碰撞。然后采用规定的性能函数，将位置误差限制在预设边界内。此外，还开发了一种学习型非矢量终端滑模控制（LNTSMC）法则，以确保位置跟踪误差的稳态和瞬态性能都符合规定的性能约束。利用迭代学习算法来更新 NN 的权重，从而降低了计算复杂度。所提出的 LNTSMC 方案有效地解决了避免航天器间碰撞、规定的动态和稳态控制性能以及鲁棒容错等问题，而不会对推进器故障施加额外的约束。本文提供了严格的稳定性分析，并通过仿真比较验证了所提方法的有效性和适用性。
{"title":"Neural network-based prescribed performance control for spacecraft formation reconfiguration with collision avoidance","authors":"Qingxian Jia , Rui Shu , Dan Yu , Chengxi Zhang , Lining Tan","doi":"10.1016/j.jfranklin.2024.107395","DOIUrl":"10.1016/j.jfranklin.2024.107395","url":null,"abstract":"<div><div>This article investigates neural network (NN)-based prescribed performance control with collision avoidance for spacecraft formation systems in the presence of space perturbations and thruster faults. First, an artificial potential function is constructed to maintain spacecraft within communication range and avoid collisions. A prescribed performance function is then employed to constrain position errors within a preset boundary. Furthermore, a learning non-singular terminal sliding mode control (LNTSMC) law is developed to ensure that both the steady-state and transient performance of position tracking errors meet the prescribed performance constraints. A novel learning NN model is incorporated to estimate and compensate for the synthesized perturbations, utilizing an iterative learning algorithm to update the weights of the NN, thereby reducing computational complexity. The proposed LNTSMC scheme effectively addresses issues of inter-spacecraft collision avoidance, prescribed dynamic and steady-state control performance, and robust fault tolerance without imposing additional constraints on thruster faults. A rigorous stability analysis is provided, and the effectiveness and applicability of the proposed method are validated through simulation comparisons.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107395"},"PeriodicalIF":3.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662795","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 : 2024-11-13DOI: 10.1016/j.jfranklin.2024.107396
Kun Shi , Luyao Yang , Zhengtian Wu , Baoping Jiang , Qing Gao
This paper presents a path planning method based on an improved simulated annealing (SA) for multi-robot navigation in a 2D plane. The method can achieve collision-free and efficient movement in environments where dynamic obstacles exist. To address the problem of considerable computational effort of general heuristic algorithms, this study improves the running process of the algorithm so that it can lock the optimal path in the process of searching for a path at a very fast speed. In addition, a prioritisation strategy is proposed for the problem of difficult coordination among multiple robots. The method has a large improvement in the coordinated operation between individual robots. Simulation tests show that the proposed method can coordinate multiple robots to avoid collisions, whilst effectively avoiding local minima and completing the task in the shortest possible time. Compared with other algorithms, the advantages of the improved SA are more obvious, and the path length obtained is about 10% shorter than other dynamic path planning algorithms, and the success rate can reach 100%.
本文提出了一种基于改进的模拟退火（SA）的路径规划方法，用于多机器人在二维平面内的导航。该方法可在存在动态障碍物的环境中实现无碰撞和高效运动。针对一般启发式算法计算量大的问题，本研究改进了算法的运行过程，使其能够在搜索路径的过程中以极快的速度锁定最优路径。此外，针对多个机器人之间难以协调的问题，还提出了一种优先级策略。该方法大大改善了单个机器人之间的协调操作。模拟测试表明，所提出的方法可以协调多个机器人避免碰撞，同时有效避免局部最小值，并在尽可能短的时间内完成任务。与其他算法相比，改进后的 SA 的优势更加明显，获得的路径长度比其他动态路径规划算法短 10%左右，成功率可达 100%。
{"title":"Multi-robot dynamic path planning with priority based on simulated annealing","authors":"Kun Shi , Luyao Yang , Zhengtian Wu , Baoping Jiang , Qing Gao","doi":"10.1016/j.jfranklin.2024.107396","DOIUrl":"10.1016/j.jfranklin.2024.107396","url":null,"abstract":"<div><div>This paper presents a path planning method based on an improved simulated annealing (SA) for multi-robot navigation in a 2D plane. The method can achieve collision-free and efficient movement in environments where dynamic obstacles exist. To address the problem of considerable computational effort of general heuristic algorithms, this study improves the running process of the algorithm so that it can lock the optimal path in the process of searching for a path at a very fast speed. In addition, a prioritisation strategy is proposed for the problem of difficult coordination among multiple robots. The method has a large improvement in the coordinated operation between individual robots. Simulation tests show that the proposed method can coordinate multiple robots to avoid collisions, whilst effectively avoiding local minima and completing the task in the shortest possible time. Compared with other algorithms, the advantages of the improved SA are more obvious, and the path length obtained is about 10% shorter than other dynamic path planning algorithms, and the success rate can reach 100%.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107396"},"PeriodicalIF":3.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702240","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 : 2024-11-12DOI: 10.1016/j.jfranklin.2024.107392
Hao Wang , Jingyi Wang , Zou Fan
Dictionary learning is a usual method in the field of machinery fault diagnosis, but it requires that the rotating speed conditions of training set and test set are the same and constant. When the speed condition of test set is different from that of training set or one of them is time-vary, normal dictionary learning is difficult to get a precise sparse representation. A special dictionary model named convolutional sparse dictionary (CSD) can overcome the influence from variable speed conditions by atoms locally shifting in the sample's dimension, which is beneficial to capture the local fault features in the signal no matter how the speed changes. However, there are both large features and small features in the mechanical vibration signal, and several continuous small features can also form a large feature. The problem is that CSD can only locally optimize the signal at a fixed scale, so the features of other scales cannot be optimized. To solve this problem, this paper proposes a model named deep convolutional sparse dictionary (DCSD) to extract bearing fault features under variable speed conditions, which is improved from CSD. DCSD has multiple dictionary layers, where each layer is a CSD, but the atom's dimensions are different in each layer. The larger the number of layer is, the larger the atom's dimension is, and the sparse representation result of each layer is used to train the next dictionary layer. Through simulations cases and experimental cases under variable speed conditions, it is proved that DCSD has better performances than CSD in the fault diagnosis.
{"title":"Deep convolutional sparse dictionary learning for bearing fault diagnosis under variable speed condition","authors":"Hao Wang , Jingyi Wang , Zou Fan","doi":"10.1016/j.jfranklin.2024.107392","DOIUrl":"10.1016/j.jfranklin.2024.107392","url":null,"abstract":"<div><div>Dictionary learning is a usual method in the field of machinery fault diagnosis, but it requires that the rotating speed conditions of training set and test set are the same and constant. When the speed condition of test set is different from that of training set or one of them is time-vary, normal dictionary learning is difficult to get a precise sparse representation. A special dictionary model named convolutional sparse dictionary (CSD) can overcome the influence from variable speed conditions by atoms locally shifting in the sample's dimension, which is beneficial to capture the local fault features in the signal no matter how the speed changes. However, there are both large features and small features in the mechanical vibration signal, and several continuous small features can also form a large feature. The problem is that CSD can only locally optimize the signal at a fixed scale, so the features of other scales cannot be optimized. To solve this problem, this paper proposes a model named deep convolutional sparse dictionary (DCSD) to extract bearing fault features under variable speed conditions, which is improved from CSD. DCSD has multiple dictionary layers, where each layer is a CSD, but the atom's dimensions are different in each layer. The larger the number of layer is, the larger the atom's dimension is, and the sparse representation result of each layer is used to train the next dictionary layer. Through simulations cases and experimental cases under variable speed conditions, it is proved that DCSD has better performances than CSD in the fault diagnosis.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107392"},"PeriodicalIF":3.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662793","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 : 2024-11-12DOI: 10.1016/j.jfranklin.2024.107383
Zhanjie Li , Jiawei Huang , Yajing Ma , Xiangpeng Xie , Dong Yue
This paper considers the constrained tracking problem for a class of stochastic nonlinear systems with non-affine terms and dead zone. The non-affine terms are not required to be differentiable, resulting in that the traditional algorithms cannot address the tracking problem efficiently. To this end, a semi-bounded condition is utilized to convert the non-affine terms into a pseudo-affine form. Moreover, the transformed systems include extra undesired spilled variables and the asymmetric dead zone input. The separation and approximation technique of neural networks are used to address this issue. By introducing a performance function, an adaptive controller is developed such that the signals of the closed-loop system are bounded in probability, and the tracking error satisfies the prescribed performance. Simulation results demonstrate the effectiveness of the proposed method.
{"title":"Prescribed tracking of stochastic nonlinear systems with indifferentiable non-affine terms and dead zone","authors":"Zhanjie Li , Jiawei Huang , Yajing Ma , Xiangpeng Xie , Dong Yue","doi":"10.1016/j.jfranklin.2024.107383","DOIUrl":"10.1016/j.jfranklin.2024.107383","url":null,"abstract":"<div><div>This paper considers the constrained tracking problem for a class of stochastic nonlinear systems with non-affine terms and dead zone. The non-affine terms are not required to be differentiable, resulting in that the traditional algorithms cannot address the tracking problem efficiently. To this end, a semi-bounded condition is utilized to convert the non-affine terms into a pseudo-affine form. Moreover, the transformed systems include extra undesired spilled variables and the asymmetric dead zone input. The separation and approximation technique of neural networks are used to address this issue. By introducing a performance function, an adaptive controller is developed such that the signals of the closed-loop system are bounded in probability, and the tracking error satisfies the prescribed performance. Simulation results demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 1","pages":"Article 107383"},"PeriodicalIF":3.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702239","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 : 2024-11-12DOI: 10.1016/j.jfranklin.2024.107401
Karim Fathi Sayeh , Salah Tamalouzt , Younes Sahri , Sofia Lalouni Belaid , Abdellah Bekhiti
This paper discusses the improvement of power quality injected into the AC grid. This approach is achieved by enhancing the quality of injected power signals and mastering the active and reactive power exchanged between the DFIG based wind turbine (WT-DFIG) and the electrical grid, resulting in an improvement of the overall system performance and efficiency. This study includes all WT-DFIG operating modes, successively and continuously, as well as all local reactive power compensation modes. Therefore, novel control strategies are proposed in this paper for wind energy conversion systems based on artificial intelligence techniques. These techniques include Neural Network Prediction (PNN-DPC) and Classification (CNN-DPC). They aim to eliminate the drawbacks and difficulties associated with conventional Direct Power Control (C-DPC), while retaining its advantages. The paper also provides a thorough explanation of the mathematical models for neural network techniques and WT-DFIG system models. The MATLAB/Simulink environment is used to investigate the performance of the proposed techniques under different conditions and operating modes related to different scenarios. The results reveal a significant reduction in the ripple of the generated active power and the compensated local reactive power, better quality of the generated signal currents and a remarkable reduction in the current total harmonic distortion (THD). Furthermore, compared to C-DPC, PNN-DPC achieves a reduction of 72.07 % in active power ripples, 77.07 % in reactive power ripples, and 76.79 % in current Total Harmonic Distortion (THD). CNN-DPC shows similar improvements with 72.04 %, 77.13 %, and 76.54 % of reductions respectively. In addition, CNN-DPC slightly outperforms PNN-DPC. Nevertheless, both proposed control techniques show significant improvements in all characteristics compared to other methods. Consequently, the proposed control strategies indicate that artificial intelligence has the potential to improve the power quality and performance of wind power conversion system.
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