Fuzzy Sets and Systems最新文献

英文中文

A locally distributed rough set model for feature selection and prototype learning 用于特征选择和原型学习的局部分布式粗糙集模型

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-30 DOI: 10.1016/j.fss.2024.109137

Shuang An , Yanhua Song , Changzhong Wang , Ge Guo

Neighborhood rough set (NRS) theory is a tool for handling data uncertainty based on neighborhood theory and has been successfully applied to feature selection and classification modeling. In practical applications, the data distribution often exhibits significant density variations, posing a challenge to the classical NRS model. To address this issue, this study proposes a locally distributed rough set (DRS) model that can adaptively select the neighborhood radius for each sample and designs data reduction algorithms accordingly. In this work, the concept of distributed neighborhood is introduced, followed by an exploration of a locally distributed rough set model based on distributed neighborhood. This model can dynamically determine the appropriate neighborhood radius for each sample based on local distribution information. Additionally, certain properties of the DRS model are summarized and proven. Subsequently, feature selection and sample reduction algorithms are developed based on the DRS model. Experimental results demonstrate the effectiveness and efficiency of these proposed algorithms, indicating that the designed DRS model is both feasible and generalizable.

邻域粗糙集（NRS）理论是一种基于邻域理论处理数据不确定性的工具，已成功应用于特征选择和分类建模。在实际应用中，数据分布往往呈现出明显的密度变化，这给经典的 NRS 模型带来了挑战。为了解决这个问题，本研究提出了一种局部分布式粗糙集（DRS）模型，它可以自适应地为每个样本选择邻域半径，并设计相应的数据缩减算法。本研究首先介绍了分布式邻域的概念，然后探讨了基于分布式邻域的局部分布式粗糙集模型。该模型可根据本地分布信息为每个样本动态确定合适的邻域半径。此外，还总结并证明了 DRS 模型的某些特性。随后，基于 DRS 模型开发了特征选择和样本缩减算法。实验结果证明了这些算法的有效性和高效性，表明所设计的 DRS 模型既可行又可推广。

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引用次数: 0

Adaptive fuzzy fixed-time control for uncertain switched nonlinear systems with non-symmetrical dead-zone 具有非对称死区的不确定开关非线性系统的自适应模糊固定时间控制

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.fss.2024.109119

Shuo Liu , Huaguang Zhang , Hongbo Pang

This paper addresses fuzzy adaptive fixed-time tracking control problem for uncertain switched nonlinear systems with non-symmetrical dead-zone, even if the tracking control problem for subsystems is not solvable. A fixed-time stability criterion for switched nonlinear systems using MLF(multiple Lyapunov functions) method is presented. Then, it is applied to fixed-time tracking control of uncertain strict-feedback switched nonlinear systems. The design methods of fuzzy adaptive feedback controllers and a state-dependent switching law are given to achieve the boundedness of all the signals of the resulting closed-loop system and the fixed-time output tracking control. Nonsymmetrical dead-zone model is used to estimate an adaptive factor through less parameters, which related to fixed-time tracking control for the uncertain switched nonlinear systems. Two examples are given to verify the effectiveness of the proposed design method.

本文探讨了具有非对称死区的不确定开关非线性系统的模糊自适应固定时间跟踪控制问题，即使子系统的跟踪控制问题无法求解。本文提出了一种使用 MLF（多重 Lyapunov 函数）方法的开关非线性系统定时稳定性准则。然后，将其应用于不确定严格反馈开关非线性系统的固定时间跟踪控制。给出了模糊自适应反馈控制器和与状态相关的开关律的设计方法，以实现闭环系统所有信号的有界性和固定时间输出跟踪控制。非对称死区模型用于通过较少的参数估计自适应因子，这与不确定开关非线性系统的固定时间跟踪控制有关。通过两个实例验证了所提设计方法的有效性。

引用次数: 0

Fixed-time self-triggered fuzzy adaptive control of N-link robotic manipulators N 连杆机器人机械手的固定时间自触发模糊自适应控制

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.fss.2024.109134

Huadi Shan , Yulian Jiang , Yanzheng Zhu , Hongjing Liang , Shenquan Wang

This paper studies the fixed-time fuzzy adaptive self-triggered control of n-link robotic manipulators. To achieve fixed-time stability, a fuzzy adaptive fixed-time control algorithm is proposed by reconstructing the self-triggered controller and using the singularity-free function, which avoids the singularity problem and obtains fixed-time stability. Meanwhile, the self-triggered mechanism reduces the communication resources between the actuator and the controller, improving the system's transmission efficiency. Through the above thoughts, a kind of fixed-time fuzzy adaptive controller based on the self-triggered mechanism is designed, which guarantees that the tracking error of each joint converges to the prescribed range within a fixed time. Finally, the effectiveness of the proposed algorithm is verified by a simulation example of the two-link robotic manipulator.

本文研究了 n 连杆机械手的固定时间模糊自适应自触发控制。为了实现定时稳定性，本文提出了一种模糊自适应定时控制算法，通过重构自触发控制器并使用无奇异性函数，避免了奇异性问题，获得了定时稳定性。同时，自触发机制减少了执行器与控制器之间的通信资源，提高了系统的传输效率。通过以上思考，设计出了一种基于自触发机制的定时模糊自适应控制器，它能保证各关节的跟踪误差在固定时间内收敛到规定范围。最后，通过双连杆机械手的仿真实例验证了所提算法的有效性。

引用次数: 0

Inversion-based fuzzy adaptive control with prespecifiable tracking accuracy for uncertain hysteretic systems 基于反演的模糊自适应控制，为不确定滞后系统提供可预设的跟踪精度

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.fss.2024.109141

Zihao Wu , Weijun Huang , Kai Huang , Zhi Liu , Guanyu Lai , Hanzhen Xiao , C.L. Philip Chen

Inversion-based control strategies have the outstanding effectiveness in the compensation for hysteresis nonlinearities. However, when the plant is driven by smart material-based actuator with the information absence of hysteresis output, there still exist technical gaps in the construction of hysteresis inverse controller. Therefore, this study aims to address this gap by proposing a novel control scheme. Technically, a novel hysteresis inverse algorithm, significantly reducing computational burden, has been proposed based on a novel adaptive estimation method for the unknown parameter (density function) in the Preisach-typed hysteresis nonlinearity. Furthermore, the inverse compensation error, the nonlinearities and uncertainties appeared in the controlled plant are accommodated by the innovative adaptive fuzzy feedback controller. With our scheme, it can ensure that the closed-loop stability, predefined steady-stated tracking performance and the convergence of algorithms including inverse algorithm and adaptive updating laws. In addition to theoretical analysis, we have validated the effectiveness of the proposed control scheme through simulation comparisons and experimental results conducted by the real-life piezoelectric actuator.

基于反演的控制策略在补偿磁滞非线性方面具有显著效果。然而，当工厂由无滞后输出信息的智能材料制动器驱动时，滞后反控制器的构建仍存在技术空白。因此，本研究旨在通过提出一种新型控制方案来弥补这一空白。在技术上，本研究提出了一种新型的磁滞反算法，该算法基于一种新型的自适应估计方法，用于估计普雷萨克型磁滞非线性中的未知参数（密度函数），从而大大减轻了计算负担。此外，创新的自适应模糊反馈控制器还能适应被控设备中出现的反向补偿误差、非线性和不确定性。通过我们的方案，可以确保闭环稳定性、预定义的稳态跟踪性能以及包括逆算法和自适应更新规律在内的算法的收敛性。除理论分析外，我们还通过仿真比较和实际压电致动器的实验结果验证了所提控制方案的有效性。

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引用次数: 0

Dual-channel event-triggered prescribed performance adaptive fuzzy time-varying formation tracking control for nonlinear multi-agent systems 非线性多代理系统的双通道事件触发规定性能自适应模糊时变编队跟踪控制

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.fss.2024.109140

Xiangjun Wu , Shuo Ding , Huanqing Wang , Ning Xu , Xudong Zhao , Wencheng Wang

This paper is concerned with the problem of dual-channel event-triggered prescribed performance adaptive fuzzy time-varying formation tracking control for multi-agent systems subject to actuator saturation, in which state variables are unmeasurable and nonlinear functions are totally unknown. A fuzzy state observer is constructed to estimate unmeasurable states. Meanwhile, fuzzy logic systems are used to approximate unknown nonlinear functions. To effectively save the usage of communication resources, this paper designs both sensor output signal and control signal triggering mechanisms, respectively. Unfortunately, the output triggering can lead to a problem that virtual control laws are non-differentiable. To solve this problem, we first utilize observer output signals to construct virtual control laws to ensure the first-order differentiation of virtual control laws. Then, a dynamic filtering technology is introduced to avoid the repeated differentiation of virtual control laws. Furthermore, an improved first-order auxiliary system is designed to compensate for the impact of actuator saturation. It is shown that the designed controller can guarantee tracking errors steer to a preset accuracy within a prescribed settling time, and all signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results verify the effectiveness of the developed control scheme.

本文关注的问题是在状态变量不可测量且非线性函数完全未知的情况下，对受执行器饱和影响的多机器人系统进行双通道事件触发的规定性能自适应模糊时变编队跟踪控制。我们构建了一个模糊状态观测器来估计不可测状态。同时，使用模糊逻辑系统来逼近未知的非线性函数。为了有效节省通信资源，本文分别设计了传感器输出信号和控制信号触发机制。遗憾的是，输出触发会导致虚拟控制法则不可分的问题。为了解决这个问题，我们首先利用观测器输出信号来构建虚拟控制律，以确保虚拟控制律的一阶微分性。然后，引入动态滤波技术，避免虚拟控制律的重复微分。此外，还设计了一个改进的一阶辅助系统来补偿执行器饱和的影响。结果表明，所设计的控制器可以保证在规定的沉降时间内跟踪误差转向预设精度，并且闭环系统中的所有信号都是半全局均匀最终约束的。最后，仿真结果验证了所开发控制方案的有效性。

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引用次数: 0

On the handling of inconsistent systems based on max-product and max-Lukasiewicz compositions 论基于最大积和最大卢卡谢维奇组合的不一致系统处理方法

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.fss.2024.109142

Ismaïl Baaj

In this article, we study the inconsistency of systems of fuzzy relational equations based either on the max-product composition or on the max-Lukasiewicz composition. Given an inconsistent system, we compute by an explicit analytical formula the Chebyshev distance (defined by L-infinity norm) between the right-hand side vector of the inconsistent system and the set of right-hand side vectors of consistent systems defined with the same matrix: that of the inconsistent system. The main result that allows us to obtain these formulas is that the Chebyshev distance is the smallest positive value that satisfies a vector inequality, whatever the t-norm used in the composition. We then give explicit analytical formulas for computing the greatest Chebyshev approximation of the right-hand side vector of an inconsistent system and its greatest approximate solution. The analytical formula of the Chebyshev distance associated with max-Lukasiewicz systems allows us to show that the fuzzy matrices which are invertible for max-Lukasiewicz composition are the permutation matrices.

在本文中，我们研究了基于最大积构成或最大卢卡谢维奇构成的模糊关系方程系统的不一致性。给定一个不一致系统，我们通过一个明确的分析公式计算出不一致系统的右侧向量与用相同矩阵定义的一致系统的右侧向量集（即不一致系统的右侧向量）之间的切比雪夫距离（由 L-infinity 准则定义）。使我们能够获得这些公式的主要结果是，切比雪夫距离是满足向量不等式的最小正值，无论在组合中使用的是什么 t 准则。然后，我们给出了计算不一致系统右边向量的最大切比雪夫近似值及其最大近似解的明确分析公式。通过与 max-Lukasiewicz 系统相关的切比雪夫距离分析公式，我们可以证明对于 max-Lukasiewicz 组合来说可逆的模糊矩阵是置换矩阵。

引用次数: 0

Quasi-D-overlap functions: Construction and characterization 准 D 叠加函数：构造与特征

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-24 DOI: 10.1016/j.fss.2024.109138

Junsheng Qiao

In this paper, we mainly consider the construction and characterization of so-called quasi-D-overlap functions, which are derived from D-overlap functions and irreducible quasi-D-overlap functions proposed by the author lately. The main contributions are: (i) it presents the concept of quasi-D-overlap functions and obtains construction manner of them by means of matrixes; (ii) it illustrates the relationship between quasi-D-overlap functions and 1-Lipschitz semi-quasi-overlap functions; (iii) it gives equivalent characterization of quasi-D-overlap functions and proper quasi-D-overlap functions by dint of matrixes, moreover, it obtains that the convex combination of quasi-D-overlap functions is also a quasi-D-overlap function.

在本文中，我们主要考虑所谓准 D 叠加函数的构造和表征，它们是从 D 叠加函数和作者最近提出的不可还原准 D 叠加函数派生出来的。其主要贡献在于(i)提出了准 D 叠加函数的概念，并通过矩阵得到了准 D 叠加函数的构造方法；(ii)说明了准 D 叠加函数与 1Lipschitz 半准叠加函数之间的关系；(iii)通过矩阵给出了准 D 叠加函数和适当准 D 叠加函数的等价表征，并得到了准 D 叠加函数的凸组合也是准 D 叠加函数。

引用次数: 0

Isomorphic triangular subnorms with continuous additive generators 具有连续相加生成器的同构三角子矩阵

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-23 DOI: 10.1016/j.fss.2024.109136

Jie Sun, Xiaoguang Liu

The additive generators play an important role in the construction of t-(sub)norms. Distinct to t-norms, the additive generators of t-subnorms need not be strictly decreasing and the value at 1 need not be 0. This paper gives the sufficient and necessary conditions such that two t-subnorms, generated by continuous additive generators, are isomorphic.

加法生成器在 t-（子）规范的构造中起着重要作用。与 t 准则不同的是，t-子准则的加法发生器不一定是严格递减的，而且在 1 处的值也不一定是 0。本文给出了两个由连续加法发生器生成的 t-子准则同构的充分必要条件。

引用次数: 0

Multi-view evidential c-means clustering with view-weight and feature-weight learning 利用视图权重和特征权重学习进行多视图证据 c-means 聚类

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-20 DOI: 10.1016/j.fss.2024.109135

Zhe Liu , Haoye Qiu , Sukumar Letchmunan , Muhammet Deveci , Laith Abualigah

Multi-view clustering remains a challenging task due to the potential overlap of clusters and variability across different views, which causes uncertainty and imprecision in cluster assignment. This paper explores multi-view evidential c-means clustering with view-weight and feature-weight learning (MVECM-VFL), grounded in the theory of belief functions (TBF). The aim is to effectively capture the uncertainty and imprecision in cluster assignment while concurrently assessing the contributions of view and feature weights in the clustering framework. We integrate view and feature weights and credal partition into a joint learning framework and design a new objective function to find the best results. In MVECM-VFL, each object can belong to different clusters with various masses of belief, thereby characterizing the uncertainty. Furthermore, when an object resides in the overlapping area of several singleton clusters, it can be attributed to a meta-cluster (defined as the union of these singleton clusters) to represent the local imprecision in cluster assignment. Additionally, view-weight and feature-weight learning can help to obtain the credal partition better. Compared to the related methods, the effectiveness of MVECM-VFL is demonstrated based on synthetic and real-world datasets.

多视图聚类仍然是一项具有挑战性的任务，因为不同视图之间可能存在聚类重叠和变异，从而导致聚类分配的不确定性和不精确性。本文以信念函数（TBF）理论为基础，探讨了具有视图权重和特征权重学习（MVECM-VFL）的多视图证据 c-means 聚类。其目的是有效捕捉聚类分配中的不确定性和不精确性，同时评估聚类框架中视图权重和特征权重的贡献。我们将视图和特征权重以及信用分区整合到一个联合学习框架中，并设计了一个新的目标函数来寻找最佳结果。在 MVECM-VFL 中，每个对象都可以以不同的信念质量属于不同的聚类，从而表征了不确定性。此外，当一个物体位于多个单子簇的重叠区域时，它可以归属于一个元簇（定义为这些单子簇的联合），以表示簇分配中的局部不精确性。此外，视图权重和特征权重学习也有助于更好地获得可信分区。与相关方法相比，MVECM-VFL 基于合成数据集和真实数据集证明了其有效性。

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Disturbance observer-based nonsingular fixed-time fuzzy adaptive event-triggered output feedback control of uncertain nonlinear systems 不确定非线性系统的基于扰动观测器的非奇异固定时间模糊自适应事件触发输出反馈控制

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems

Pub Date : 2024-09-19 DOI: 10.1016/j.fss.2024.109132

Ming-Rui Liu , Li-Bing Wu , Huan-Qing Wang , Liang-Dong Guo , Sheng-Juan Huang

This article examines the fuzzy adaptive event-triggered output feedback control issue of eliminating fixed-time singularity for a type of uncertain nonlinear systems with disturbance observer structures. By introducing novel bounded time-varying functions (TVFs), a set of more general intermediate-variable-based disturbance observers (IVBDOs) is constructed. Combining the corresponding auxiliary reduced-power function and the quartic Lyapunov method, a co-design scheme for a fuzzy approximation high-order controller and an improved event-triggered mechanism with a judgment indicator threshold is proposed. Especially, the developed framework not only removes the singularity during the fixed-time design process but also further reduces the communication resources. By means of theoretical analysis, the devised solution achieves fixed-time stable control (FTSC) of the system and the tracking error converges to the desired neighborhood around the origin. After verifying the absence of Zeno behavior, the efficacy of the presented methodology is supported by two simulation examples.

本文研究了具有扰动观测器结构的一类不确定非线性系统消除固定时间奇异性的模糊自适应事件触发输出反馈控制问题。通过引入新颖的有界时变函数（TVF），构建了一套更通用的基于中间变量的扰动观测器（IVBDO）。结合相应的辅助减幂函数和四次方 Lyapunov 方法，提出了模糊逼近高阶控制器和带判断指标阈值的改进事件触发机制的协同设计方案。特别是，所开发的框架不仅消除了定时设计过程中的奇异性，还进一步减少了通信资源。通过理论分析，所设计的方案实现了系统的定时稳定控制（FTSC），跟踪误差收敛到了原点附近的理想邻域。在验证了不存在 Zeno 行为后，两个仿真实例证明了所提出方法的有效性。

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