Feedback and adaptive control for the synchronization of Chen system via a single variable

Wang, Yan‐Wu; Guan, Zhi‐Hong; Wang, Hua O.

doi:10.1016/s0375-9601(03)00573-5

Cited by 172 publications

(77 citation statements)

References 13 publications

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“…13 Chaos, its control and synchronization for a fractional-order rotational machine system with a centrifugal governor is investigated. 5 Moreover, the OGY method, 14 linear and nonlinear feedback control, 15,16 adaptive method 17 and time-delay feedback control 18 are considered as the efficient tools for controlling chaotic oscillation. However, precision model and accurate parameters are the prerequisite in the process of design and the states trajectories of the system can converge to zero when time is tending towards infinity.…”

Section: Introductionmentioning

confidence: 99%

Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

2016

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This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the “explosion of complexity” of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

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Section: Introductionmentioning

confidence: 99%

Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

2016

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“…studied synchronization of bidirectionally coupled chaotic Chen's system with delay in 2007 [9] and they also observed synchronization of generalised linearly bidirectionally coupled unified chaotic system in 2009 [10]. Synchronization via adaptive control has been successfully tested in variety of non-linear dynamical systems including Unified chaotic system, Lu system and Chen system [11,12,13]. In 1994 J.K.John and R.E.Amritkar have studied synchronization of unstable orbits using adaptive control [14].…”

Section: Introductionmentioning

confidence: 99%

Adaptive synchronization of two coupled Newton-Leipnik systems with uncertain parameter

Khan¹

2012

International Journal of Basic and Applied Sciences

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In this letter, an adaptive synchronization and parameters identification scheme is proposed for two coupled chaotic Newton-Leipnik systems. Based on Lyapunov stability theory an adaptive controller is designed to make the states of two identical chaotic Newton-Leipnik system with unknown system parameters asymptotically synchronized. Especially when some unknown parameters are positive, we can make the controller more simple, beside the controller is independent of those positive uncertain parameters. Numerical simulation results are presented to visualize the effectiveness and feasibility of the developed approaches.

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“…Five models have been commonly used to investigate synchronization: the Hodgkin-Huxley [21], [44], Kuramoto [1], [8], [38], Lorenz [17], [23], [41], Fitzhugh-Nagumo [24], [37], and Hindmarsh-Rose [10], [12], [13], [31] models. Note that the first two models are not in polynomial form while the rest are.…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, the resulting feedback laws for synchronization are in the form of linear feedback or linear feedback with variable gain ( [2], [4], [14], [17], [23], [25], [41], [43]). Secondly, feedback interaction is unidirectional ( [39], [40]) in the sense that a reference model without input is employed for synchronization.…”

Section: Introductionmentioning

confidence: 99%

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A Nonlinear Synchronization Scheme for Hindmarsh-Rose Models

Kim¹,

Allgöwer²

2010

Journal of Electrical Engineering and Technology

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-Multiple subsystems are required to behave synchronously or cooperatively in many areas. For example, synchronous behaviors are common in networks of (electro-) mechanical systems, cell biology, coupled neurons, and cooperating robots. This paper presents a feedback scheme for synchronization between Hindmarsh-Rose models which have polynomial vector fields. We show that the problem is equivalent to finding an asymptotically stabilizing control for error dynamics which is also a polynomial system. Then, an extension to a nonlinear observer-based scheme is presented, which reduces the amount of information exchange between models.

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Feedback and adaptive control for the synchronization of Chen system via a single variable

Cited by 172 publications

References 13 publications

Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

Adaptive synchronization of two coupled Newton-Leipnik systems with uncertain parameter

A Nonlinear Synchronization Scheme for Hindmarsh-Rose Models

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