Pub Date : 2024-10-29DOI: 10.1016/j.chaos.2024.115687
Xincheng Shu, Man Yang, Zhongyuan Ruan, Qi Xuan
Threshold-driven models and game theory are two fundamental paradigms for describing human interactions in social systems. However, in mimicking social contagion processes, models that simultaneously incorporate these two mechanisms have been largely overlooked. Here, we study a general model that integrates hybrid interaction forms by assuming that a part of nodes in a network are driven by the threshold mechanism, while the remaining nodes exhibit imitation behavior governed by their rationality (under the game-theoretic framework). Our results reveal that the spreading dynamics are determined by the payoff of adoption. For positive payoffs, increasing the density of highly rational nodes can promote the adoption process, accompanied by a double phase transition. The degree of rationality can regulate the spreading speed, with less rational imitators slowing down the spread. We further find that the results are opposite for negative payoffs of adoption. This model may provide valuable insights into understanding the complex dynamics of social contagion phenomena in real-world social networks.
{"title":"Social contagion under hybrid interactions","authors":"Xincheng Shu, Man Yang, Zhongyuan Ruan, Qi Xuan","doi":"10.1016/j.chaos.2024.115687","DOIUrl":"10.1016/j.chaos.2024.115687","url":null,"abstract":"<div><div>Threshold-driven models and game theory are two fundamental paradigms for describing human interactions in social systems. However, in mimicking social contagion processes, models that simultaneously incorporate these two mechanisms have been largely overlooked. Here, we study a general model that integrates hybrid interaction forms by assuming that a part of nodes in a network are driven by the threshold mechanism, while the remaining nodes exhibit imitation behavior governed by their rationality (under the game-theoretic framework). Our results reveal that the spreading dynamics are determined by the payoff of adoption. For positive payoffs, increasing the density of highly rational nodes can promote the adoption process, accompanied by a double phase transition. The degree of rationality can regulate the spreading speed, with less rational imitators slowing down the spread. We further find that the results are opposite for negative payoffs of adoption. This model may provide valuable insights into understanding the complex dynamics of social contagion phenomena in real-world social networks.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115687"},"PeriodicalIF":5.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142537759","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 : 2024-10-29DOI: 10.1016/j.chaos.2024.115673
Ning Yu , Xue Zhang
This paper presents a tick-borne disease transmission model with a Filippov-type control strategy that involves spraying insecticides to kill ticks once the number of infected hosts exceeds a certain threshold. The model also incorporates two delays in disease transmission: an internal delay representing the maturation period of pathogens inside ticks, and an external delay accounting for the time from a host being bitten by an infected tick to becoming infectious. Theoretical analysis deduces that the endemic equilibrium of the delayed Filippov system may undergo a Hopf bifurcation as the delays exceed critical levels. Furthermore, based on Filippov’s convex analysis, the sliding mode dynamics of the system are explored. The results indicate that depending on the threshold levels, the system’s solutions eventually converge to either the regular equilibrium of the two subsystems, a pseudo-equilibrium on the sliding mode, or a stable periodic solution. From a numerical perspective, the system undergoes different boundary focus bifurcation under different time delays and thresholds. Moreover, variations in the delay can lead to the emergence of a global sliding bifurcation on the sliding mode. Therefore, a Filippov system with multiple delays provides new insights and directions for controlling the spread of tick-borne diseases.
{"title":"Complex dynamics in tick-borne disease transmission: A Filippov-type control strategy model with multiple time delays","authors":"Ning Yu , Xue Zhang","doi":"10.1016/j.chaos.2024.115673","DOIUrl":"10.1016/j.chaos.2024.115673","url":null,"abstract":"<div><div>This paper presents a tick-borne disease transmission model with a Filippov-type control strategy that involves spraying insecticides to kill ticks once the number of infected hosts exceeds a certain threshold. The model also incorporates two delays in disease transmission: an internal delay <span><math><mrow><msub><mrow><mi>τ</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo></mrow></math></span> representing the maturation period of pathogens inside ticks, and an external delay <span><math><mrow><msub><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msub><mo>,</mo></mrow></math></span> accounting for the time from a host being bitten by an infected tick to becoming infectious. Theoretical analysis deduces that the endemic equilibrium of the delayed Filippov system may undergo a Hopf bifurcation as the delays exceed critical levels. Furthermore, based on Filippov’s convex analysis, the sliding mode dynamics of the system are explored. The results indicate that depending on the threshold levels, the system’s solutions eventually converge to either the regular equilibrium of the two subsystems, a pseudo-equilibrium on the sliding mode, or a stable periodic solution. From a numerical perspective, the system undergoes different boundary focus bifurcation under different time delays and thresholds. Moreover, variations in the delay can lead to the emergence of a global sliding bifurcation on the sliding mode. Therefore, a Filippov system with multiple delays provides new insights and directions for controlling the spread of tick-borne diseases.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115673"},"PeriodicalIF":5.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142537757","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 : 2024-10-29DOI: 10.1016/j.chaos.2024.115688
Jinlong Ma , Hongfei Zhao
Inspired by the complex interplay between reputation and social proximity, we propose a novel model called the Manhattan distance reputation circle, integrating nonlinear reputation mechanisms and interaction range within the spatial prisoner’s dilemma game. In this model, the average reputation of neighbors sharing the same strategy within a specific Manhattan distance is incorporated into the central node’s strategy update rule. Two rules are introduced to evaluate average reputation: rule A employs the standard averaging method, while rule B applies a distance-based decay, introducing a nonlinear weighting to the reputation, giving more influence to closer neighbors. Monte Carlo simulations reveal that the proposed model exhibits nonlinear dynamics that promote the emergence of cooperative strategies. Specifically, greater interaction range and reputation adjustment values enhance cooperation, although the impact of interaction range plateaus beyond a certain threshold. While both rules foster cooperation, rule B’s nonlinear reputation decay reduces the fluctuations in cooperation seen in rule A as increases under high introduction rates in the model.
受声誉和社会邻近性之间复杂相互作用的启发，我们提出了一个名为曼哈顿距离声誉圈的新模型，将非线性声誉机制和互动范围整合到空间囚徒困境博弈中。在这个模型中，特定曼哈顿距离内共享相同策略的邻居的平均声誉被纳入中心节点的策略更新规则。该模型引入了两种规则来评估平均声誉：规则 A 采用标准的平均法，而规则 B 则采用基于距离的衰减法，对声誉进行非线性加权，使距离较近的邻居具有更大的影响力。蒙特卡洛模拟显示，所提出的模型呈现出非线性动态，促进了合作策略的出现。具体来说，更大的互动范围和声誉调整值会促进合作，尽管互动范围的影响在超过一定临界值后会趋于平稳。虽然两种规则都能促进合作，但规则 B 的非线性声誉衰减减少了规则 A 在模型中高引入率下随着 α 的增加而出现的合作波动。
{"title":"Cooperation dynamics of reputation-based manhattan distance social circle in spatial prisoner’s dilemma game in evolutionary game theory","authors":"Jinlong Ma , Hongfei Zhao","doi":"10.1016/j.chaos.2024.115688","DOIUrl":"10.1016/j.chaos.2024.115688","url":null,"abstract":"<div><div>Inspired by the complex interplay between reputation and social proximity, we propose a novel model called the Manhattan distance reputation circle, integrating nonlinear reputation mechanisms and interaction range within the spatial prisoner’s dilemma game. In this model, the average reputation of neighbors sharing the same strategy within a specific Manhattan distance is incorporated into the central node’s strategy update rule. Two rules are introduced to evaluate average reputation: rule A employs the standard averaging method, while rule B applies a distance-based decay, introducing a nonlinear weighting to the reputation, giving more influence to closer neighbors. Monte Carlo simulations reveal that the proposed model exhibits nonlinear dynamics that promote the emergence of cooperative strategies. Specifically, greater interaction range and reputation adjustment values enhance cooperation, although the impact of interaction range plateaus beyond a certain threshold. While both rules foster cooperation, rule B’s nonlinear reputation decay reduces the fluctuations in cooperation seen in rule A as <span><math><mi>α</mi></math></span> increases under high introduction rates in the model.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115688"},"PeriodicalIF":5.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142537758","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 : 2024-10-29DOI: 10.1016/j.chaos.2024.115694
Bo Qin , Ying Zhang
The objective of this work is to deeply investigate the sensitivity to initial conditions and the factors influencing the level of chaos in a double pendulum system from a novel global perspective. Firstly, the pendulum's motion trajectories and mechanical energy are compared to determine the appropriate numerical algorithms for solving this model, including the fourth-order Runge-Kutta method (RK4 method) and the Euler method. Secondly, the captured experimental motion trajectories, along with numerical results, vividly demonstrate the system's sensitivity to initial conditions. On this basis, we develop an algorithm that successfully delineates the basins of attraction associated with the number of flips and the final angular positions of the pendulum, uncovering a petal-like structure characterized by significant rotational symmetry and fractal features. Finally, we employ a heat map of the average maximum Lyapunov exponent to reveal the correlation between mass ratio and the level of chaos. Both qualitative and quantitative results consistently confirm the mechanisms underlying the system's sensitivity to initial conditions and the reliability of the developed algorithm. This research provides valuable insights into the global dynamics and engineering applications of the double pendulum system.
{"title":"A novel global perspective: Characterizing the fractal basins of attraction and the level of chaos in a double pendulum","authors":"Bo Qin , Ying Zhang","doi":"10.1016/j.chaos.2024.115694","DOIUrl":"10.1016/j.chaos.2024.115694","url":null,"abstract":"<div><div>The objective of this work is to deeply investigate the sensitivity to initial conditions and the factors influencing the level of chaos in a double pendulum system from a novel global perspective. Firstly, the pendulum's motion trajectories and mechanical energy are compared to determine the appropriate numerical algorithms for solving this model, including the fourth-order Runge-Kutta method (RK4 method) and the Euler method. Secondly, the captured experimental motion trajectories, along with numerical results, vividly demonstrate the system's sensitivity to initial conditions. On this basis, we develop an algorithm that successfully delineates the basins of attraction associated with the number of flips and the final angular positions of the pendulum, uncovering a petal-like structure characterized by significant rotational symmetry and fractal features. Finally, we employ a heat map of the average maximum Lyapunov exponent to reveal the correlation between mass ratio and the level of chaos. Both qualitative and quantitative results consistently confirm the mechanisms underlying the system's sensitivity to initial conditions and the reliability of the developed algorithm. This research provides valuable insights into the global dynamics and engineering applications of the double pendulum system.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115694"},"PeriodicalIF":5.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142537756","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 : 2024-10-28DOI: 10.1016/j.chaos.2024.115680
Lin Wang , Yin-Ling Liu , Xiao-Fen Lin , Rui-Wu Wang
Mutualistic relationships between species have always fascinated ecologists because of the key role they play in ecosystem functioning. Early studies on the mutualism focused on the mutual influences and constraints between mutualistic parties and the environment. In fact, ecological and evolutionary processes may occur at the same time scale, which means that the coupling of these two processes needs to be fully considered. However, it is still a lack of coupled population dynamics and phenotypic trait dynamics of species to explore maintenance mechanisms of the mutualism. Here, we developed an eco-evolutionary model to investigate intrinsic driving forces for the maintenance of fig-wasp mutualism by coupling population dynamics, phenotypic trait (i.e., style and ovipositor) evolution, and Allee effect of the fig tree. Theoretical results found that: (i) the presence of the Allee effect contributes to the stabilisation of mutualistic relationships in the fig-wasp system; (ii) the fig-wasp mutualism is more prone to oscillation when the evolutionary rate of the style is greater than that of the ovipositor, and population dynamics of mutualistic parties are mainly dominated by interspecific interactions; (iii) under a relatively harsh environment, the eco-evolutionary model predicts the coexistence of species, whereas the ecological model does not. Our work suggests that eco-evolutionary feedbacks have an important effect on the stability of ecosystems, with a view to providing theoretical support for the understanding of interspecific interactions in general mutualistic systems and for the conservation of biodiversity.
{"title":"Eco-evolutionary feedbacks promotes species coexistence in the fig-wasp mutualism with Allee effect","authors":"Lin Wang , Yin-Ling Liu , Xiao-Fen Lin , Rui-Wu Wang","doi":"10.1016/j.chaos.2024.115680","DOIUrl":"10.1016/j.chaos.2024.115680","url":null,"abstract":"<div><div>Mutualistic relationships between species have always fascinated ecologists because of the key role they play in ecosystem functioning. Early studies on the mutualism focused on the mutual influences and constraints between mutualistic parties and the environment. In fact, ecological and evolutionary processes may occur at the same time scale, which means that the coupling of these two processes needs to be fully considered. However, it is still a lack of coupled population dynamics and phenotypic trait dynamics of species to explore maintenance mechanisms of the mutualism. Here, we developed an eco-evolutionary model to investigate intrinsic driving forces for the maintenance of fig-wasp mutualism by coupling population dynamics, phenotypic trait (i.e., style and ovipositor) evolution, and Allee effect of the fig tree. Theoretical results found that: (<em>i</em>) the presence of the Allee effect contributes to the stabilisation of mutualistic relationships in the fig-wasp system; (<em>ii</em>) the fig-wasp mutualism is more prone to oscillation when the evolutionary rate of the style is greater than that of the ovipositor, and population dynamics of mutualistic parties are mainly dominated by interspecific interactions; (<em>iii</em>) under a relatively harsh environment, the eco-evolutionary model predicts the coexistence of species, whereas the ecological model does not. Our work suggests that eco-evolutionary feedbacks have an important effect on the stability of ecosystems, with a view to providing theoretical support for the understanding of interspecific interactions in general mutualistic systems and for the conservation of biodiversity.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115680"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535214","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}
This paper presents a synchronizing approach to chaotic systems with unknown nonlinear dynamics using a Gaussian non-singleton type-3 (NT3) fuzzy logic system (T3-FLS). The proposed method effectively addresses the challenges of parameter uncertainties and external disturbances by utilizing higher-order fuzzy approximations, thereby enhancing robustness and adaptability. By incorporating a projection operator, the control scenario ensures stability. The design includes a fixed-time adaptive synchronization technique that guarantees convergence in a predetermined time frame, independent of the initial values. The presented theoretical analysis proves the superiority of the designed synchronization approach, while simulations demonstrate significant improvements in synchronization performance and resilience against uncertainties. Specifically, the proposed method achieves root mean square errors of 0.1990 and 0.2754 for the tracking errors, representing improvements over 30% compared to the other benchmarking methods. These outcomes demonstrate the robustness of our proposed controller in handling chaotic systems under various operating conditions.
{"title":"A non-singleton type-3 neuro-fuzzy fixed-time synchronizing method","authors":"Hamid Taghavifar , Ardashir Mohammadzadeh , Chunwei Zhang","doi":"10.1016/j.chaos.2024.115671","DOIUrl":"10.1016/j.chaos.2024.115671","url":null,"abstract":"<div><div>This paper presents a synchronizing approach to chaotic systems with unknown nonlinear dynamics using a Gaussian non-singleton type-3 (NT3) fuzzy logic system (T3-FLS). The proposed method effectively addresses the challenges of parameter uncertainties and external disturbances by utilizing higher-order fuzzy approximations, thereby enhancing robustness and adaptability. By incorporating a projection operator, the control scenario ensures stability. The design includes a fixed-time adaptive synchronization technique that guarantees convergence in a predetermined time frame, independent of the initial values. The presented theoretical analysis proves the superiority of the designed synchronization approach, while simulations demonstrate significant improvements in synchronization performance and resilience against uncertainties. Specifically, the proposed method achieves root mean square errors of 0.1990 and 0.2754 for the tracking errors, representing improvements over 30% compared to the other benchmarking methods. These outcomes demonstrate the robustness of our proposed controller in handling chaotic systems under various operating conditions.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115671"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535212","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 : 2024-10-28DOI: 10.1016/j.chaos.2024.115677
Tianping Zhang , Wei Zhang
In this paper, adaptive practical prescribed-time (PPT) control is proposed for a class of uncertain nonlinear systems with time-varying parameters and unmodeled dynamics. By constructing a novel time-varying scaling function and utilizing nonlinear mapping, the PPT control is successfully resolved. The dynamical uncertainties resulting from unmodeled dynamics are estimated by employing an auxiliary available signal, and the unknown continuous terms are handled by the aid of radial basis function neural networks (RBFNNs). A novel adaptive control method is developed by introducing the compensating signals and dynamic surface control as well as practical prescribed-time control. All the signals involved are proved to be semi-globally uniformly ultimately bounded, and the tracking error could enter the pre-specified convergence region within a pre-specified time. The robotic manipulator system is used to demonstrate the effectiveness of the proposed control approach.
{"title":"Adaptive practical prescribed-time control for uncertain nonlinear systems with time-varying parameters","authors":"Tianping Zhang , Wei Zhang","doi":"10.1016/j.chaos.2024.115677","DOIUrl":"10.1016/j.chaos.2024.115677","url":null,"abstract":"<div><div>In this paper, adaptive practical prescribed-time (PPT) control is proposed for a class of uncertain nonlinear systems with time-varying parameters and unmodeled dynamics. By constructing a novel time-varying scaling function and utilizing nonlinear mapping, the PPT control is successfully resolved. The dynamical uncertainties resulting from unmodeled dynamics are estimated by employing an auxiliary available signal, and the unknown continuous terms are handled by the aid of radial basis function neural networks (RBFNNs). A novel adaptive control method is developed by introducing the compensating signals and dynamic surface control as well as practical prescribed-time control. All the signals involved are proved to be semi-globally uniformly ultimately bounded, and the tracking error could enter the pre-specified convergence region within a pre-specified time. The robotic manipulator system is used to demonstrate the effectiveness of the proposed control approach.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115677"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535886","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 : 2024-10-28DOI: 10.1016/j.chaos.2024.115693
Jiaqi Liu, Qianwei Zhang, Rui Tang
Punishing selfish individuals is regarded as an effective method to maintain social cooperation. In reality, the corresponding punishment probability should vary with different game environments. However, most current research treats this probability as a constant or exogenously given. In this paper, based on the public goods game, we design an environmental feedback mechanism and establish a feedback evolutionary game model. The model assumes that the probability of punishing defectors will change with the proportion of cooperators, ultimately influencing individual decision-making. Through theoretical analysis and numerical simulations, we obtain three stable states of the system under different parameter conditions: a state of complete defection with low punishment probability, a state of complete cooperation with high punishment probability, and a bistable state. Our research results indicate that the environmental feedback mechanism plays a crucial role in promoting long-term social stability and sustainable development.
{"title":"Fostering cooperative evolution through probabilistic punishment and environmental feedback in public goods game","authors":"Jiaqi Liu, Qianwei Zhang, Rui Tang","doi":"10.1016/j.chaos.2024.115693","DOIUrl":"10.1016/j.chaos.2024.115693","url":null,"abstract":"<div><div>Punishing selfish individuals is regarded as an effective method to maintain social cooperation. In reality, the corresponding punishment probability should vary with different game environments. However, most current research treats this probability as a constant or exogenously given. In this paper, based on the public goods game, we design an environmental feedback mechanism and establish a feedback evolutionary game model. The model assumes that the probability of punishing defectors will change with the proportion of cooperators, ultimately influencing individual decision-making. Through theoretical analysis and numerical simulations, we obtain three stable states of the system under different parameter conditions: a state of complete defection with low punishment probability, a state of complete cooperation with high punishment probability, and a bistable state. Our research results indicate that the environmental feedback mechanism plays a crucial role in promoting long-term social stability and sustainable development.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115693"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535213","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 : 2024-10-28DOI: 10.1016/j.chaos.2024.115696
Muhammad Aown Ali , Naveed Ishtiaq Chaudhary , Taimoor Ali Khan , Wei-Lung Mao , Chien-Chou Lin , Muhammad Asif Zahoor Raja
Fractional calculus generalizes the conventional calculus to real order and become a popular tool for efficient modeling of complex engineering problems by providing better insight to the system through involving historical information. In this study, fractional calculus concepts are incorporated into input nonlinear output error (INOE) system and is generalized to fractional INOE (FINOE) model through Grunwald-Letnikov differential operator. The key-term-separation based identification model is presented to estimate the parameters of FINOE system that avoids the burden of identifying extra parameters due to cross product terms. The parameter estimation of systems modeled by Hammerstein output error structure is a challenging task, especially with incorporation of fractional concepts. An auxiliary model based Runge Kutta (RUN) optimization methodology is proposed for viable estimation of FINOE parameters by using the estimate for unmeasurable terms of information vector. The mean-square-error based fitness function is developed that minimizes the difference between the actual and estimated responses of the FINOE system. The efficacy of the proposed scheme is investigated in terms of convergence speed, computational cost, resilience, stability and correctness in approximation of accurate weights of the FINOE system for multiple noise variations. The superiority of the RUN for FINOE is endorsed via comparative analysis with 8 states of the arts in noisy environments.
{"title":"Design of key term separated identification model for fractional input nonlinear output error systems: Auxiliary model based Runge Kutta optimization algorithm","authors":"Muhammad Aown Ali , Naveed Ishtiaq Chaudhary , Taimoor Ali Khan , Wei-Lung Mao , Chien-Chou Lin , Muhammad Asif Zahoor Raja","doi":"10.1016/j.chaos.2024.115696","DOIUrl":"10.1016/j.chaos.2024.115696","url":null,"abstract":"<div><div>Fractional calculus generalizes the conventional calculus to real order and become a popular tool for efficient modeling of complex engineering problems by providing better insight to the system through involving historical information. In this study, fractional calculus concepts are incorporated into input nonlinear output error (INOE) system and is generalized to fractional INOE (FINOE) model through Grunwald-Letnikov differential operator. The key-term-separation based identification model is presented to estimate the parameters of FINOE system that avoids the burden of identifying extra parameters due to cross product terms. The parameter estimation of systems modeled by Hammerstein output error structure is a challenging task, especially with incorporation of fractional concepts. An auxiliary model based Runge Kutta (RUN) optimization methodology is proposed for viable estimation of FINOE parameters by using the estimate for unmeasurable terms of information vector. The mean-square-error based fitness function is developed that minimizes the difference between the actual and estimated responses of the FINOE system. The efficacy of the proposed scheme is investigated in terms of convergence speed, computational cost, resilience, stability and correctness in approximation of accurate weights of the FINOE system for multiple noise variations. The superiority of the RUN for FINOE is endorsed via comparative analysis with 8 states of the arts in noisy environments.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115696"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535215","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 : 2024-10-25DOI: 10.1016/j.chaos.2024.115649
Junwen Xiao, Yongchao Liu
This paper presents a self-triggered consensus resilient control method for nonlinear multi-agent systems (MASs) under sensor deception attacks. A single parameter learning method is integrated into backstepping technique to simplify design procedure. The neural networks are utilized to compensate for unknown dynamics of the MASs. Moreover, a self-triggered mechanism is presented for MASs to refrain from continuously monitoring triggering conditions and conserve communication resources. The designed controller can resist sensor deception attacks and guarantee that all signals of the MASs are uniformly bounded. An expository simulation example reveals the virtue of the presented method.
本文针对传感器欺骗攻击下的非线性多代理系统（MAS）提出了一种自触发共识弹性控制方法。为了简化设计程序，本文将单参数学习方法集成到反步进技术中。利用神经网络对 MAS 的未知动态进行补偿。此外，还为 MAS 提出了一种自触发机制，以避免持续监控触发条件并节省通信资源。所设计的控制器可以抵御传感器欺骗攻击，并保证 MAS 的所有信号都是均匀有界的。一个说明性仿真实例揭示了所提出方法的优点。
{"title":"Self-triggered consensus resilient control for multi-agent systems against sensor deception attacks based on a single parameter learning method","authors":"Junwen Xiao, Yongchao Liu","doi":"10.1016/j.chaos.2024.115649","DOIUrl":"10.1016/j.chaos.2024.115649","url":null,"abstract":"<div><div>This paper presents a self-triggered consensus resilient control method for nonlinear multi-agent systems (MASs) under sensor deception attacks. A single parameter learning method is integrated into backstepping technique to simplify design procedure. The neural networks are utilized to compensate for unknown dynamics of the MASs. Moreover, a self-triggered mechanism is presented for MASs to refrain from continuously monitoring triggering conditions and conserve communication resources. The designed controller can resist sensor deception attacks and guarantee that all signals of the MASs are uniformly bounded. An expository simulation example reveals the virtue of the presented method.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115649"},"PeriodicalIF":5.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535203","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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