Sliding mode synchronization of multiple chaotic systems with uncertainties and disturbances

Chen, Xiangyong; Park, Ju H.; Cao, Jinde; Qiu, Jianlong

doi:10.1016/j.amc.2017.03.032

Cited by 103 publications

(65 citation statements)

References 23 publications

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“…where σ 2 k ð Þ ¼ σ 2 k ð ÞN 2 H 0 , η 2 is a positive constant, the design parameter b ζ 2 is the estimation of ζ 2 , and ζ 2 is expressed as 13) and the sign function is defined as sign…”

Section: Design Of State Observermentioning

confidence: 99%

“…Hence, the problem of robust stabilization and tracking control for uncertain nonlinear systems has been widely investigated. Over the past decades, a range of research has been undertaken in this field . However, these studies assumed that all system states are known.…”

Section: Introductionmentioning

confidence: 99%

“…Over the past decades, a range of research has been undertaken in this field. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] However, these studies assumed that all system states are known. From a practical point of view, the system states may not be available and only the system outputs can be measured in many systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

Pai

2018

Asian Journal of Control

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A new discrete‐time adaptive global sliding mode control (SMC) scheme combined with a state observer is proposed for the robust stabilization of uncertain nonlinear systems with mismatched time delays and input nonlinearity. A state observer is developed to estimate the unmeasured system states. By using Lyapunov stability theorem and linear matrix inequality (LMI), the condition for the existence of quasi‐sliding mode is derived and the stability of the overall closed‐loop system is guaranteed. Finally, simulation results are presented to demonstrate the validity of the proposed scheme.

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Section: Design Of State Observermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

Pai

2018

Asian Journal of Control

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“…[26][27][28][29][30][31][32] Besides, it is shown that chaotic characteristic 33,34 has discovered in numerous fractional-order systems like the fractional-order Arneodo system, the fractional-order Lorenz system, and the fractional-order Lu system. [26][27][28][29][30][31][32] Besides, it is shown that chaotic characteristic 33,34 has discovered in numerous fractional-order systems like the fractional-order Arneodo system, the fractional-order Lorenz system, and the fractional-order Lu system.…”

Section: Introductionmentioning

confidence: 99%

Composite learning fuzzy synchronization for incommensurate fractional‐order chaotic systems with time‐varying delays

Zhou

Liu

Cao

et al. 2019

Adaptive Control & Signal

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This paper presents a composite learning fuzzy control to synchronize two different uncertain incommensurate fractional-order time-varying delayed chaotic systems with unknown external disturbances and mismatched parametric uncertainties via the Takagi-Sugeno fuzzy method. An adaptive controller together with fractional-order composite learning laws is designed based on both a parallel distributed compensation technology and a fractional Lyapunov criterion. The boundedness of all variables in the closed-loop system and the Mittag-Leffler stability of tracking error can be guaranteed. T-S fuzzy systems are provided to tackle unknown nonlinear functions. The distinctive features of the proposed approach consist in the following: (1) a supervisory control law is designed to compensate the lumped disturbances; (2) both the prediction error and the tracking error are used to estimate the unknown fuzzy system parameters; (3) parameter convergence can be ensured by an interval excitation condition. Finally, the feasibility of the proposed control strategy is demonstrated throughout an illustrative example.

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“…The synchronization and anti-synchronization via active control approach on fractional chaotic financial system were studied by Huang et al in [21]. On the basis of control theory, a lot of methods, such as adaptive control [22], sliding control [23,24], pinning control [25], intermittent control [26,27], have been developed for CS.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural network synchronization for uncertain strick-feedback chaotic systems subject to dead-zone input

2018

Adv Differ Equ

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In this paper, an adaptive neural network (NN) synchronization controller is designed for two identical strict-feedback chaotic systems (SFCSs) subject to dead-zone input. The dead-zone models together with the system uncertainties are approximated by NNs. The dynamic surface control (DSC) approach is applied in the synchronization controller design, and the traditional problem of "explosion of complexity" that usually occurs in the backstepping design can be avoided. The proposed synchronization method guarantees the synchronization errors tend to an arbitrarily small region. Finally, this paper presents two simulation examples to confirm the effectiveness and the robustness of the proposed control method.

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Sliding mode synchronization of multiple chaotic systems with uncertainties and disturbances

Cited by 103 publications

References 23 publications

Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

Composite learning fuzzy synchronization for incommensurate fractional‐order chaotic systems with time‐varying delays

Adaptive neural network synchronization for uncertain strick-feedback chaotic systems subject to dead-zone input

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