Synchronisation of uncertain chaotic systems via fuzzy-regulated adaptive optimal control approach

Hai-Yun, Zhang; Meng, Deyuan; Wang, Jin; Lu, Guodong

doi:10.1080/00207721.2020.1716104

Cited by 9 publications

(4 citation statements)

References 33 publications

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“…According to Lyapunov stability theory, we select a Lyapunov function V(t) = 0.5S T (t)S(t) > 0 for all S(t) = 0. Obviously, condition (16) implies that .…”

Section: Robust Smc Controller Designmentioning

confidence: 99%

“…For satisfying the hitting condition (16), the SMC control input subjected to bounded uncertainty is proposed as…”

Section: V(t) = S T (T)mentioning

confidence: 99%

“…These disturbances often cause degradation or even failure of the control performance. Therefore, designing a robust control scheme to asymptotically suppress or eliminate the influence of unknown disturbances is a very important issue when discussing synchronization control for chaotic systems [16], and some research works have been proposed by studying the effects of input uncertainties [17][18][19]. By considering the uncertainties for control inputs, the state synchronization controller for two identical n-dimensional chaotic systems was proposed in [17], and the robust adaptive finite-time controller was reported for synchronization in [18].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Synchronization Errors between Master and Slave Chaotic Systems with Matched/Mismatched Disturbances and Input Uncertainty

Lin

Yan

2021

Mathematics

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This study is concerned with robust synchronization for master–slave chaotic systems with matched/mismatched disturbances and uncertainty in the control input. A robust sliding mode control (SMC) is presented to achieve chaos synchronization even under the influence of matched/mismatched disturbances and uncertainty of inputs. A proportional-integral (PI) switching surface is introduced to make the controlled error dynamics in the sliding manifold easy to analyze. Furthermore, by using the proposed SMC scheme even subjected to input uncertainty, we can force the trajectories of the error dynamics to enter the sliding manifold and fully synchronize the master–slave systems in spite of matched uncertainties and input nonlinearity. As for the mismatched disturbances, the bounds of synchronization errors can be well estimated by introducing the limit of the Riemann sum, which is not well addressed in previous works. Simulation experiments including matched and mismatched cases are presented to illustrate the robustness and synchronization performance with the proposed SMC synchronization controller.

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“…According to Lyapunov stability theory, we select a Lyapunov function V(t) = 0.5S T (t)S(t) > 0 for all S(t) = 0. Obviously, condition (16) implies that .…”

Section: Robust Smc Controller Designmentioning

confidence: 99%

“…For satisfying the hitting condition (16), the SMC control input subjected to bounded uncertainty is proposed as…”

Section: V(t) = S T (T)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Synchronization Errors between Master and Slave Chaotic Systems with Matched/Mismatched Disturbances and Input Uncertainty

Lin

Yan

2021

Mathematics

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“…In terms of chaos synchronization techniques, various approaches have been proposed in the literature. For instance, sliding mode control [8], digital redesign control [9], optimal control [10], backstepping method [11], impulsive control [12], intermittent scheme [13], switching process [14], composite nonlinear feedback [10], fuzzy-logic control [15] and neuralbased control [16] have been considered. Sliding mode control (SMC) is an effective robust control technique which has been used for the synchronization or control of chaos in power electronic systems [17,18], touchless fingerprint encryption [19], satellite motion [20], cryptosystem [21], wind speed forecasting [22], Van der Pol oscillator [23], wind power interval prediction [24], nonlinear pendulum [25], image encryption [26], secure communication [27,28] and so on.…”

Section: Introductionmentioning

confidence: 99%

Fast Reaching Finite Time synchronization Approach for Chaotic Systems With Application in Medical Image Encryption

et al. 2021

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This article proposes a fast reaching finite time synchronization approach for chaotic systems along with its application to medical image encryption. First, an adaptive terminal sliding mode tracking approach with fast reaching condition is designed to synchronize the chaotic systems at the transmitter and receiver ends in finite time. Then, a chaotic cryptosystem, using synchronized chaotic systems as secret keys generator, is proposed to enhance the security of medical image transmission and/or storage. The applicability and efficiency of the proposed synchronization approach is assessed using a simulation as well as an analytical study. The analysis encompassed security tools such as histogram analysis, correlation test, and information entropy change the rate of the number of pixels and unified average changing intensity. The obtained results confirmed the robustness and fast convergence rate of the proposed synchronization approach. The security analysis also shows that the proposed cryptosystem displays acceptable levels of resistance to various attacks. INDEX TERMSChaos synchronization; fast reaching condition; medical image encryption; MORE method encryption.

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A novel probabilistic analysis method for long-term dynamical response analysis

Meng,

Jin

2024

Acta Mech

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Synchronisation of uncertain chaotic systems via fuzzy-regulated adaptive optimal control approach

Cited by 9 publications

References 33 publications

Estimation of Synchronization Errors between Master and Slave Chaotic Systems with Matched/Mismatched Disturbances and Input Uncertainty

Estimation of Synchronization Errors between Master and Slave Chaotic Systems with Matched/Mismatched Disturbances and Input Uncertainty

Fast Reaching Finite Time synchronization Approach for Chaotic Systems With Application in Medical Image Encryption

A novel probabilistic analysis method for long-term dynamical response analysis

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