In this paper, the impact of nonlinear components is studied for cooperative load transportation systems with any number of quadrotors and a single slung load suspended by ropes. The main goal is to control and estimate constraints caused by the nonlinear term of the load transportation system. A novel distributed control strategy is proposed for cooperative systems based on adaptive fuzzy wavelet networks (AFWNs). Distributed AFWNs are employed to compensate for nonlinear effects. Another result is the expansion of the system’s attraction region for the initial state values. Also, by employing an integral term in the control law, the formation error of the agents converges to zero. These expansions allow the system to significantly improve its robustness to disturbances. The simulation results illustrate that the proposed method can keep the agents in desired formation and guide the load in right direction.
{"title":"Adaptive fuzzy wavelet network control for nonlinear cooperative load transportation systems","authors":"Matin Fadavi , Majdeddin Najafi , Farid Sheikholeslam","doi":"10.1016/j.fss.2025.109681","DOIUrl":"10.1016/j.fss.2025.109681","url":null,"abstract":"<div><div>In this paper, the impact of nonlinear components is studied for cooperative load transportation systems with any number of quadrotors and a single slung load suspended by ropes. The main goal is to control and estimate constraints caused by the nonlinear term of the load transportation system. A novel distributed control strategy is proposed for cooperative systems based on adaptive fuzzy wavelet networks (AFWNs). Distributed AFWNs are employed to compensate for nonlinear effects. Another result is the expansion of the system’s attraction region for the initial state values. Also, by employing an integral term in the control law, the formation error of the agents converges to zero. These expansions allow the system to significantly improve its robustness to disturbances. The simulation results illustrate that the proposed method can keep the agents in desired formation and guide the load in right direction.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"527 ","pages":"Article 109681"},"PeriodicalIF":2.7,"publicationDate":"2025-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-15DOI: 10.1016/j.fss.2025.109682
Hua-Peng Zhang , Yao Ouyang
After mining some inherent properties of the class of uninorms on a bounded lattice, we present structural representation theorems for uninorms in by distinguishing two cases. As an application of the representation theorems, we propose several construction methods for uninorms in . These results can be easily translated into their counterparts for uninorms in via the Duality Principle in poset theory.
{"title":"Representation and construction of the classes Umin1 and Umax0 of uninorms on a bounded lattice","authors":"Hua-Peng Zhang , Yao Ouyang","doi":"10.1016/j.fss.2025.109682","DOIUrl":"10.1016/j.fss.2025.109682","url":null,"abstract":"<div><div>After mining some inherent properties of the class <span><math><msubsup><mi>U</mi><mrow><mi>min</mi></mrow><mrow><mspace></mspace><mn>1</mn></mrow></msubsup></math></span> of uninorms on a bounded lattice, we present structural representation theorems for uninorms in <span><math><msubsup><mi>U</mi><mrow><mi>min</mi></mrow><mrow><mspace></mspace><mn>1</mn></mrow></msubsup></math></span> by distinguishing two cases. As an application of the representation theorems, we propose several construction methods for uninorms in <span><math><msubsup><mi>U</mi><mrow><mi>min</mi></mrow><mrow><mspace></mspace><mn>1</mn></mrow></msubsup></math></span>. These results can be easily translated into their counterparts for uninorms in <span><math><msubsup><mi>U</mi><mrow><mi>max</mi></mrow><mrow><mspace></mspace><mn>0</mn></mrow></msubsup></math></span> via the Duality Principle in poset theory.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"529 ","pages":"Article 109682"},"PeriodicalIF":2.7,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-14DOI: 10.1016/j.fss.2025.109679
M.D.M. Bibiloni-Femenias , O. Valero
In the literature there are two different approaches that extend the classical crisp notion of equivalence relation to the fuzzy framework. On the one hand, one can find the notion of indistinguishability operator and a few of its generalizations. These can be understood as a kind of measurement of the degree of similarity or indistinguishability between objects. On the other hand, fuzzy (quasi-)metrics measure such a degree with respect to a parameter. The study of both types of the aforesaid notions has been carried out independently without any connection between them. As a consequence, the notion of modular indistinguishability operator has been introduced recently. Such a notion unifies under the same framework both aforesaid similarity concepts. In this paper, we explore the aggregation problem for modular indistinguishability operators and for several generalizations. Hence we introduce the notions of modular fuzzy pre-order, modular fuzzy partial order and modular equality and we characterize the functions that are able to fuse all these different types of modular similarities. The aforementioned characterizations are stated in terms of triangular triplets or related notions, monotony and dominance. In contrast to the non-modular case, the class of those functions that merge modular fuzzy pre-orders (modular fuzzy partial orders) is shown to match the class of modular indistinguishability operators (modular equalities). Furthermore, the relationships between the non-modular aggregation problem, the modular one and the fuzzy metric aggregation problem are explored and the differences between them are clarified by means of appropriate examples.
{"title":"Modular indistinguishability: The aggregation problem","authors":"M.D.M. Bibiloni-Femenias , O. Valero","doi":"10.1016/j.fss.2025.109679","DOIUrl":"10.1016/j.fss.2025.109679","url":null,"abstract":"<div><div>In the literature there are two different approaches that extend the classical crisp notion of equivalence relation to the fuzzy framework. On the one hand, one can find the notion of indistinguishability operator and a few of its generalizations. These can be understood as a kind of measurement of the degree of similarity or indistinguishability between objects. On the other hand, fuzzy (quasi-)metrics measure such a degree with respect to a parameter. The study of both types of the aforesaid notions has been carried out independently without any connection between them. As a consequence, the notion of modular indistinguishability operator has been introduced recently. Such a notion unifies under the same framework both aforesaid similarity concepts. In this paper, we explore the aggregation problem for modular indistinguishability operators and for several generalizations. Hence we introduce the notions of modular fuzzy pre-order, modular fuzzy partial order and modular equality and we characterize the functions that are able to fuse all these different types of modular similarities. The aforementioned characterizations are stated in terms of triangular triplets or related notions, monotony and dominance. In contrast to the non-modular case, the class of those functions that merge modular fuzzy pre-orders (modular fuzzy partial orders) is shown to match the class of modular indistinguishability operators (modular equalities). Furthermore, the relationships between the non-modular aggregation problem, the modular one and the fuzzy metric aggregation problem are explored and the differences between them are clarified by means of appropriate examples.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109679"},"PeriodicalIF":2.7,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-14DOI: 10.1016/j.fss.2025.109678
Jih-Jeng Huang , Chin-Yi Chen
We introduce a unified framework extending the classical Choquet integral by incorporating Stieltjes-type accumulation functions and dual set-functions. This construction, termed the dual Choquet–Stieltjes (DCS) integral, broadens non-additive integral theory, allowing simultaneous treatment of threshold-dependent behaviors and asymmetric interactions. We prove fundamental properties including well-definedness, monotonicity, and comonotonic additivity under precisely specified conditions. We establish convergence theorems (monotone convergence, Fatou’s lemma, dominated convergence) with complete proofs, and demonstrate applications in decision-making. Our framework generalizes existing extensions under a single, coherent approach that maintains theoretical properties while enhancing modeling flexibility. Through parameter recovery studies, we demonstrate the theoretical soundness of our approach and identify scenarios where the full DCS framework is necessary to capture complex interdependencies and threshold effects.
{"title":"The choquet–Stieltjes integral with dual set-Functions: a unified theory and applications","authors":"Jih-Jeng Huang , Chin-Yi Chen","doi":"10.1016/j.fss.2025.109678","DOIUrl":"10.1016/j.fss.2025.109678","url":null,"abstract":"<div><div>We introduce a unified framework extending the classical Choquet integral by incorporating Stieltjes-type accumulation functions and dual set-functions. This construction, termed the dual Choquet–Stieltjes (DCS) integral, broadens non-additive integral theory, allowing simultaneous treatment of threshold-dependent behaviors and asymmetric interactions. We prove fundamental properties including well-definedness, monotonicity, and comonotonic additivity under precisely specified conditions. We establish convergence theorems (monotone convergence, Fatou’s lemma, dominated convergence) with complete proofs, and demonstrate applications in decision-making. Our framework generalizes existing extensions under a single, coherent approach that maintains theoretical properties while enhancing modeling flexibility. Through parameter recovery studies, we demonstrate the theoretical soundness of our approach and identify scenarios where the full DCS framework is necessary to capture complex interdependencies and threshold effects.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109678"},"PeriodicalIF":2.7,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-13DOI: 10.1016/j.fss.2025.109680
Raquel Fernandez-Peralta , Andrea Mesiarová-Zemánková
Fuzzy implication functions constitute fundamental operators in fuzzy logic systems, extending classical conditionals to manage uncertainty in logical inference. Among the extensive families of these operators, generalizations of the classical material implication have received considerable theoretical attention, particularly (S, N)-implications constructed from t-conorms and fuzzy negations, and their further generalizations to (U, N)-implications using disjunctive uninorms. Prior work has established characterization theorems for these families under the assumption that the fuzzy negation N is continuous, ensuring uniqueness of representation. In this paper, we disprove this last fact for (U, N)-implications and we show that they do not necessarily possess a unique representation, even if the fuzzy negation is continuous. Further, we provide a comprehensive study of uniqueness conditions for both uninorms with continuous and non-continuous underlying functions. Our results offer important theoretical insights into the structural properties of these operators.
{"title":"On the non-uniqueness of representation of (U, N)-implications","authors":"Raquel Fernandez-Peralta , Andrea Mesiarová-Zemánková","doi":"10.1016/j.fss.2025.109680","DOIUrl":"10.1016/j.fss.2025.109680","url":null,"abstract":"<div><div>Fuzzy implication functions constitute fundamental operators in fuzzy logic systems, extending classical conditionals to manage uncertainty in logical inference. Among the extensive families of these operators, generalizations of the classical material implication have received considerable theoretical attention, particularly (<em>S, N</em>)-implications constructed from t-conorms and fuzzy negations, and their further generalizations to (<em>U, N</em>)-implications using disjunctive uninorms. Prior work has established characterization theorems for these families under the assumption that the fuzzy negation <em>N</em> is continuous, ensuring uniqueness of representation. In this paper, we disprove this last fact for (<em>U, N</em>)-implications and we show that they do not necessarily possess a unique representation, even if the fuzzy negation is continuous. Further, we provide a comprehensive study of uniqueness conditions for both uninorms with continuous and non-continuous underlying functions. Our results offer important theoretical insights into the structural properties of these operators.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109680"},"PeriodicalIF":2.7,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1016/j.fss.2025.109675
Shengda Tang , Zihan Chen , Hai Wang , Jun Cheng
This article develops a novel fuzzy stochastic structurally-sparse sliding mode control (FS4MC) scheme for the malicious attacks-injected interconnected multi-area power systems (IMAPSs). In response to the nonlinear characteristics of valve position deviation and the uncertain switching feature of the inter-area feedback communication network (FCN), an interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy IMAPS model with the Markov jump structurally-sparse FCN topology is established. Subsequently, FS4MC compensation strategy is developed for this model to counteract the impact of attack signals, ensuring the finite-time reachability of the ideal sliding surface and the stochastic stability of the IT-2 T-S fuzzy IMAPS with switching FCN topology. On the other hand, since the FS4MC scheme design relies on IMAPS dynamics, which is frequently unavailable, a data-centric algorithm is developed to compute this scheme without requiring either model information or an initially stabilizing policy pair. Finally, the case study on a three-area IMAPS demonstrates the effectiveness of the proposed method.
{"title":"Reinforcement learning-based stochastic structurally-sparse sliding mode control for IT-2 T-S fuzzy interconnected multi-area power system","authors":"Shengda Tang , Zihan Chen , Hai Wang , Jun Cheng","doi":"10.1016/j.fss.2025.109675","DOIUrl":"10.1016/j.fss.2025.109675","url":null,"abstract":"<div><div>This article develops a novel fuzzy stochastic structurally-sparse sliding mode control (FS<sup>4</sup>MC) scheme for the malicious attacks-injected interconnected multi-area power systems (IMAPSs). In response to the nonlinear characteristics of valve position deviation and the uncertain switching feature of the inter-area feedback communication network (FCN), an interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy IMAPS model with the Markov jump structurally-sparse FCN topology is established. Subsequently, FS<sup>4</sup>MC compensation strategy is developed for this model to counteract the impact of attack signals, ensuring the finite-time reachability of the ideal sliding surface and the stochastic stability of the IT-2 T-S fuzzy IMAPS with switching FCN topology. On the other hand, since the FS<sup>4</sup>MC scheme design relies on IMAPS dynamics, which is frequently unavailable, a data-centric algorithm is developed to compute this scheme without requiring either model information or an initially stabilizing policy pair. Finally, the case study on a three-area IMAPS demonstrates the effectiveness of the proposed method.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109675"},"PeriodicalIF":2.7,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-08DOI: 10.1016/j.fss.2025.109674
Dingxin He , Haoping Wang , Yang Tian , Minxuan Zha , Radu-Emil Precup
Aiming at the trajectory tracking problem of the mechatronic systems in the presence of uncertainties, matched and mismatched disturbances, and input nonlinearities, a fractional-order ultra-local model-based direct adaptive fuzzy controller (FO-DAFC) is proposed in this paper. To reduce the difficulty of controller design, the fractional-order ultra-local model is constructed to reformulate the complex mechatronic system. Then, a global sliding surface is proposed to eliminates the reaching phase and ensures the global robustness. Furthermore, an ideal global sliding mode controller is designed to converge the tracking error. However, the unknown and unmeasured parameters are existed in the ideal controller. The fuzzy logic system is thus established to approximate the ideal control law. And the fuzzy weight adaptive law is designed by using gradient descent method. Correspondingly, the direct adaptive fuzzy controller is proposed. After that, the stability of the closed-loop system with the proposed FO-DAFC is analyzed through using Lyapunov theorem. Ultimately, the numerical simulation of 2-DOF robotic manipulator with different input nonlinearities and co-simulation of 4-DOF robotic manipulator compared with other controllers are completed. The obtained results demonstrate the effectiveness and superiority of the proposed controller.
{"title":"Fractional-order ultra-local model-based direct adaptive fuzzy sliding mode control for mechatronic systems with mismatched disturbances and input nonlinearities","authors":"Dingxin He , Haoping Wang , Yang Tian , Minxuan Zha , Radu-Emil Precup","doi":"10.1016/j.fss.2025.109674","DOIUrl":"10.1016/j.fss.2025.109674","url":null,"abstract":"<div><div>Aiming at the trajectory tracking problem of the mechatronic systems in the presence of uncertainties, matched and mismatched disturbances, and input nonlinearities, a fractional-order <em>ultra-local model</em>-based direct adaptive fuzzy controller (FO-DAFC) is proposed in this paper. To reduce the difficulty of controller design, the fractional-order <em>ultra-local model</em> is constructed to reformulate the complex mechatronic system. Then, a global sliding surface is proposed to eliminates the reaching phase and ensures the global robustness. Furthermore, an ideal global sliding mode controller is designed to converge the tracking error. However, the unknown and unmeasured parameters are existed in the ideal controller. The fuzzy logic system is thus established to approximate the ideal control law. And the fuzzy weight adaptive law is designed by using gradient descent method. Correspondingly, the direct adaptive fuzzy controller is proposed. After that, the stability of the closed-loop system with the proposed FO-DAFC is analyzed through using Lyapunov theorem. Ultimately, the numerical simulation of 2-DOF robotic manipulator with different input nonlinearities and co-simulation of 4-DOF robotic manipulator compared with other controllers are completed. The obtained results demonstrate the effectiveness and superiority of the proposed controller.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109674"},"PeriodicalIF":2.7,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.fss.2025.109665
Jiaying Wang , Zhehuang Huang , Zhifeng Weng , Jinjin Li
As a typical multi-granularity data analysis model, multi-scale decision systems have received widespread attention from researchers in recent years. However, most multi-scale models struggle to handle continuous data and fail to accurately characterize the differences between samples in complex scenes. Moreover, there is a lack of investigation on fuzzy multi-scale uncertainty measures, as well as their application in dimension reduction. Motivated by these issues, we put forth a new multi-scale fuzzy relation decision system and investigate the uncertainty measures for fuzzy relation families at different scales. To this end, δ-fuzzy similarity relationship is presented to characterize the correlation of target objects. Fuzzy scale entropy is then proposed to reflect the distinguishing ability of fuzzy relation families with different scales. Some variants of the uncertainty measure, such as joint fuzzy scale entropy, conditional fuzzy scale entropy, and mutual fuzzy scale entropy, are then presented to reveal the relationship between the distinguishing ability of feature subsets. Finally, a knowledge reduction algorithm for multi-scale fuzzy relation decision systems is developed from the perspective of maintaining the distinguishing ability. Extensive experiments on 16 public datasets exhibit that our model can effectively reduce redundant features from different scales, and demonstrates competitive classification performance compared with four state-of-the-art dimension reduction algorithms.
{"title":"Feature subset selection using fuzzy scale entropy-Based uncertainty measures for multi-scale fuzzy relation decision systems","authors":"Jiaying Wang , Zhehuang Huang , Zhifeng Weng , Jinjin Li","doi":"10.1016/j.fss.2025.109665","DOIUrl":"10.1016/j.fss.2025.109665","url":null,"abstract":"<div><div>As a typical multi-granularity data analysis model, multi-scale decision systems have received widespread attention from researchers in recent years. However, most multi-scale models struggle to handle continuous data and fail to accurately characterize the differences between samples in complex scenes. Moreover, there is a lack of investigation on fuzzy multi-scale uncertainty measures, as well as their application in dimension reduction. Motivated by these issues, we put forth a new multi-scale fuzzy relation decision system and investigate the uncertainty measures for fuzzy relation families at different scales. To this end, <em>δ</em>-fuzzy similarity relationship is presented to characterize the correlation of target objects. Fuzzy scale entropy is then proposed to reflect the distinguishing ability of fuzzy relation families with different scales. Some variants of the uncertainty measure, such as joint fuzzy scale entropy, conditional fuzzy scale entropy, and mutual fuzzy scale entropy, are then presented to reveal the relationship between the distinguishing ability of feature subsets. Finally, a knowledge reduction algorithm for multi-scale fuzzy relation decision systems is developed from the perspective of maintaining the distinguishing ability. Extensive experiments on 16 public datasets exhibit that our model can effectively reduce redundant features from different scales, and demonstrates competitive classification performance compared with four state-of-the-art dimension reduction algorithms.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109665"},"PeriodicalIF":2.7,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.fss.2025.109653
Weiling Bao , Shoucheng Yuan , Dian Zhang , Jun Cheng , Dan Zhang , Yu Fu
This paper addresses the challenges of hybrid cyberattacks on fuzzy systems, focusing on observer-based security control strategies enhanced by adaptive neural networks. A generalized multi-mode denial-of-service (DoS) attack model is developed, utilizing a variable matrix to represent diverse attack ranges across multiple communication channels, with sojourn probabilities employed to describe attack stochasticity, thus offering an alternative to traditional Markov models. The study also investigates unknown deception attacks, incorporating an online weight-adjusting neural network to estimate and counteract the adverse effects of these malicious inputs. Furthermore, a dynamic mismatch model framework is introduced to accurately characterize the evolving discrepancies between actual and estimated DoS attack modes, addressing the limitations of prior fixed mismatch assumptions. The findings present a robust foundation for enhancing the resilience of fuzzy systems against hybrid cyberattacks, providing significant implications for future research in network security. On this basis, by using Lyapunov theory, sufficient criteria that guarantee the boundedness of the closed-loop fuzzy system are established. Finally, the effectiveness and the superiority of the designed control strategy are verified by the tunnel diode circuit model.
{"title":"Adaptive neural security control of fuzzy systems with sojourn-probability-Based multi-mode attacks","authors":"Weiling Bao , Shoucheng Yuan , Dian Zhang , Jun Cheng , Dan Zhang , Yu Fu","doi":"10.1016/j.fss.2025.109653","DOIUrl":"10.1016/j.fss.2025.109653","url":null,"abstract":"<div><div>This paper addresses the challenges of hybrid cyberattacks on fuzzy systems, focusing on observer-based security control strategies enhanced by adaptive neural networks. A generalized multi-mode denial-of-service (DoS) attack model is developed, utilizing a variable matrix to represent diverse attack ranges across multiple communication channels, with sojourn probabilities employed to describe attack stochasticity, thus offering an alternative to traditional Markov models. The study also investigates unknown deception attacks, incorporating an online weight-adjusting neural network to estimate and counteract the adverse effects of these malicious inputs. Furthermore, a dynamic mismatch model framework is introduced to accurately characterize the evolving discrepancies between actual and estimated DoS attack modes, addressing the limitations of prior fixed mismatch assumptions. The findings present a robust foundation for enhancing the resilience of fuzzy systems against hybrid cyberattacks, providing significant implications for future research in network security. On this basis, by using Lyapunov theory, sufficient criteria that guarantee the boundedness of the closed-loop fuzzy system are established. Finally, the effectiveness and the superiority of the designed control strategy are verified by the tunnel diode circuit model.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"526 ","pages":"Article 109653"},"PeriodicalIF":2.7,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.fss.2025.109661
Huichao Lin , Jiuxiang Dong , Ju H. Park
This paper considers the stability and stabilization issues of T-S fuzzy systems with time-varying delays. A preassigned-delay-subinterval-based Lyapunov functional is constructed to capture more effective delay information. This Lyapunov functional uses different matrix pairs in different time-varying delay subintervals, so that each delay subinterval has its own Lyapunov functional, which relaxes the constraint of traditional Lyapunov functional using the same matrix pair in each delay subinterval. By employing this approach, the functional not only provides a concise hierarchical form but also eliminates the need to manually design different Lyapunov functionals for various N. Additionally, by utilizing the characteristics of the preassigned delay subintervals, a delay-product-type matrix is introduced into the Lyapunov functional. This technique relaxes the positive definiteness constraint of the Lyapunov matrix. Based on this, a hierarchical stability and stabilization criterion is derived for the T-S fuzzy system with N preassigned delay subintervals. Finally, three examples are used to test the superiority of the obtained stability and stabilization criteria.
{"title":"Hierarchical stability and stabilization criteria for delayed T-S fuzzy systems via preassigned-delay-subinterval-based Lyapunov functional","authors":"Huichao Lin , Jiuxiang Dong , Ju H. Park","doi":"10.1016/j.fss.2025.109661","DOIUrl":"10.1016/j.fss.2025.109661","url":null,"abstract":"<div><div>This paper considers the stability and stabilization issues of T-S fuzzy systems with time-varying delays. A preassigned-delay-subinterval-based Lyapunov functional is constructed to capture more effective delay information. This Lyapunov functional uses different matrix pairs in different time-varying delay subintervals, so that each delay subinterval has its own Lyapunov functional, which relaxes the constraint of traditional Lyapunov functional using the same matrix pair in each delay subinterval. By employing this approach, the functional not only provides a concise hierarchical form but also eliminates the need to manually design different Lyapunov functionals for various <em>N</em>. Additionally, by utilizing the characteristics of the preassigned delay subintervals, a delay-product-type matrix is introduced into the Lyapunov functional. This technique relaxes the positive definiteness constraint of the Lyapunov matrix. Based on this, a hierarchical stability and stabilization criterion is derived for the T-S fuzzy system with <em>N</em> preassigned delay subintervals. Finally, three examples are used to test the superiority of the obtained stability and stabilization criteria.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"525 ","pages":"Article 109661"},"PeriodicalIF":2.7,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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