Adaptive Predefined-Time Synchronization of Two Different Fractional-Order Chaotic Systems With Time-Delay

Lin, Lixiong; Wang, Qing; He, Bingwei; Chen, Yanjie; Peng, Xiafu; Mei, Ruilin

doi:10.1109/access.2021.3059324

Cited by 27 publications

(13 citation statements)

References 43 publications

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“…The chaotic attractor of system (24). control in [30]; and (4) the proposed scheme in this paper. By comparing the three different schemes, it can be concluded that the control scheme proposed in this paper is characterized by fast speed.…”

Section: Predefined-time Synchronization Of Fo Pmsmmentioning

confidence: 99%

“…In order to better illustrate the fast convergence of the proposed scheme in this paper for FO systems, we compare the convergence times of several SMC schemes with similar control parameters. In Table 1, we denote the convergence time of each error term by

T_{italicei} (i = 1, 2, 3)

: (1) finite‐time control in [12]; (2) fixed‐time control in [20]; (3) scheduled‐time control in [30]; and (4) the proposed scheme in this paper. By comparing the three different schemes, it can be concluded that the control scheme proposed in this paper is characterized by fast speed.…”

Section: Numerical Simulationmentioning

confidence: 99%

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Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Chen,

Zhao,

Xiao

2024

Math Methods in App Sciences

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Based on the fractional calculus and sliding mode control (SMC) techniques, this paper presents a predefined‐time synchronization scheme for fractional‐order chaotic systems (FOCSs). Firstly, a predefined‐time control method is proposed for fractional‐order systems. Subsequently, a novel sliding surface is presented to ensure predefined‐time convergence of the synchronization error. Then, a controller is designed by combining the predefined‐time stability and the SMC method to ensure that the synchronization error converges to zero within the predefined time. Finally, the feasibility and robustness of the scheme are illustrated with two numerical simulation examples.

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Section: Predefined-time Synchronization Of Fo Pmsmmentioning

confidence: 99%

T_{italicei} (i = 1, 2, 3)

Section: Numerical Simulationmentioning

confidence: 99%

Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Chen,

Zhao,

Xiao

2024

Math Methods in App Sciences

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“…Wang et al, 2020). In addition, chaos-based fractional order synchronization has also been investigated in different studies (Lin et al, 2021(Lin et al, , 2022Meng et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Fractional Order Analysis of the 4-Dimensional Hyperchaotic Pang System and Its Adaptive Synchronization

Yılmaz,

Günay

2024

UUJFE

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Fractional calculus is an effective method used to analyze the dynamics of nonlinear systems and provide more precise results. In this study, firstly, the 4-dimensional Pang system is introduced and its dynamic analyses demonstrating the hyperchaotic structure are given. Then, fractional-order calculations of the system are presented and the dynamics of the system for different fraction orders are investigated. At this point, according to the results obtained from Lyapunov exponents and phase-space representation, the Pang system exhibits periodic, chaotic, and hyperchaotic behaviors in different fractional orders. The results obtained at the end of this study present that the system is hyperchaotic for the fractional order of 3.52 and it is also confirmed that more accurate results are obtained than the integer-order analysis. In the next part of the study, adaptive synchronization of the fractional-order system is performed. Three different cases are examined and it is demonstrated that synchronization is achieved in all cases.

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“…[30] considered the control problem of fractional order systems with time-varying delays. [31] studied two different fractional order chaotic systems synchronization with time delay and introduced the delayed function to solve time delay.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Adaptive Neural Network Backstepping Sliding Mode Control for Fractional Order Chaotic Systems Synchronization With Input Delay

2021

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This paper investigates the fractional order chaotic systems synchronization with input delay. To reduce the utilization of communication resources and achieve system synchronization, an adaptive neural network backstepping sliding mode controller is proposed based on event-triggered scheme without Zeno behavior. To avoid ''explosion of complexity'' and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. The sliding term is introduced to enhance robustness. The Pade delay approximation method is used to handle the input delay, which can reduce the analysis complexity of fractional order chaotic systems with input delay. The unknown nonlinear functions and uncertain disturbances are approximated by the RBF neural network. An observer is used for state estimation of the fractional order system. By applying the Lyapunov stability theory, we can prove that the all closed-loop signals are bounded. Examples and simulations prove the feasibility of the proposed control method.INDEX TERMS Fractional order chaotic systems synchronization, event-triggered, dynamic surface control, neural network, observer, input delay.

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Adaptive Predefined-Time Synchronization of Two Different Fractional-Order Chaotic Systems With Time-Delay

Cited by 27 publications

References 43 publications

Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Fractional Order Analysis of the 4-Dimensional Hyperchaotic Pang System and Its Adaptive Synchronization

Event-Triggered Adaptive Neural Network Backstepping Sliding Mode Control for Fractional Order Chaotic Systems Synchronization With Input Delay

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