Simple effective Zhang-dynamics stabilization control of the 4th-order hyper-chaotic Lu system with one input

Zhang, Yunong; Qiao, Tianjian; Zhang, Deyang; Tan, Hongzhou; Dong, Liqun

doi:10.1109/fskd.2016.7603195

Cited by 6 publications

(6 citation statements)

References 12 publications

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“…Note that most of the specific chaotic systems could be formulated as the master chaotic system (1) with a general form of nonlinear differential equations, such as Lu chaotic systems [53], Chen chaotic systems [55], and Lorenz chaotic systems [56], which covers most common chaotic systems [31].…”

Section: Preliminaries and Neurodynamic Approachesmentioning

confidence: 99%

“…In addition, there is no parameter selection limitation during the design process of the control system. Compared with other approaches [14,31,53,54,55,56,71], the above-mentioned advantages make the controller (6) designed by the proposed SEZN approach more suitable for practical applications of the real-time synchronization of chaotic systems with the requirement of fast computational speed.…”

Section: Verifications Comparisons and Testsmentioning

confidence: 99%

“…Due to the advantages in terms of distributed storage, parallelism and easy implementation by the hardware, the neurodynamic approach has been served as a prior alternative for chaotic synchronization of sensor systems by researchers as well as engineers [37,38,39,40,41,42,43,44,45]. As the new branch of recurrent-neural-networks (RNNs) [46,47,48,49], various neural network models designed by the CZN approach have been developed as effective tools for the online engineering issues handling, as well as real-time synchronization of chaotic systems [50,51,52,53,54,55,56]. For instance, Zhang et al [53] detailedly investigated the control issues of three kinds of chaotic systems by combining the CZN approach as well as the gradient neurodynamic approach to design an effective controller.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Zhang et al [53] detailedly investigated the control issues of three kinds of chaotic systems by combining the CZN approach as well as the gradient neurodynamic approach to design an effective controller. Moreover, an effective stabilization control method of the hyper-chaotic system with only-one control-input was investigated in [55] by using a neurodynamic approach. Jin et al [56] novelly proposed a controller-design approach, for tracking-control of a modified Lorenz chaotic system with the division by zero problem conquered.…”

Section: Introductionmentioning

confidence: 99%

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Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

Chen

2018

Sensors

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Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach inherently possesses the advantage of super-exponential convergence property, which makes the synchronization process faster and more accurate. Theoretical analyses on the stability and convergence advantages in terms of both faster convergence speed and lower error bound within the task duration are rigorously presented. Moreover, three synchronization examples substantiate the validity of the SEZN approach and the related controller for synchronization of chaotic sensor systems. Comparisons with other approaches such as the CZN approach, show the convergence superiority of the proposed SEZN approach. Finally, extensive tests further investigate the impact on convergence performance by choosing different values of design parameter and initial state.

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Section: Preliminaries and Neurodynamic Approachesmentioning

confidence: 99%

Section: Verifications Comparisons and Testsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

Chen

2018

Sensors

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“…For instances, Zhang et al [50] detailedly investigated the tracking control problems of Lorenz, Chen and Lu chaotic systems via combining the CZN approach and gradient neurodynamic approach for developing an effective controller. In addition, a simple stabilization control approach of hyper-chaotic Lu system with one control input was proposed in [51] by employing the neurodynamic approach. Jin et al [52] novelly proposed an effective controller design approach for the tracking control of a modified Lorenz nonlinear system in consideration of singularities (or termed division by zero issue) handling.…”

Section: Introductionmentioning

confidence: 99%

A Novel Disturbance Rejection Zeroing Neurodynamic Approach for Robust Synchronization of Chaotic Systems

Chen¹,

Li²,

Wu³

2019

IEEE Access

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Robust synchronization of chaotic systems becomes a hot topic in scientific and engineering fields because of the ubiquitous existence of time-variant external disturbances in complex application scenarios. In contrast with existing studies that the resultant synchronization error has a supremum or even diverges under the influence of time-variant external disturbances, this paper proposes a disturbance rejection zeroing neurodynamic (DRZN) approach and its related controller for the robust synchronization of chaotic systems against time-variant external disturbances. The controller designed by the proposed DRZN approach distinctively features the rejection of external disturbances with the generated synchronization error being convergence toward zero. Theoretical analyses guarantee that the DRZN approach and its related controller inherently possess robustness. Moreover, numerical studies including three examples substantiate the effectiveness of the proposed DRZN approach and its related controller for the synchronization of chaotic systems against the time-variant external disturbances. Comparisons with existing approaches, e.g., the conventional zeroing neurodynamic (CZN) approach and the linear-active control (LAC) approach, show the superiority of the proposed DRZN approach. Extensive tests further verify that the proposed DRZN approach possesses the outstanding anti-disturbance performance, and thus is suitable for the practical applications with time-variant external disturbances.INDEX TERMS Zeroing neurodynamic approach, robustness, zeroing neural networks, chaotic systems, external disturbances.

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ZG Stabilization of TVL System with PDBZ Shown

Zhang

Qiu

2020

Zhang-Gradient Control

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Simple effective Zhang-dynamics stabilization control of the 4th-order hyper-chaotic Lu system with one input

Cited by 6 publications

References 12 publications

Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

Rejecting Chaotic Disturbances Using a Super-Exponential-Zeroing Neurodynamic Approach for Synchronization of Chaotic Sensor Systems

A Novel Disturbance Rejection Zeroing Neurodynamic Approach for Robust Synchronization of Chaotic Systems

ZG Stabilization of TVL System with PDBZ Shown

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