Neural networks adaptive synchronization for four-dimension energy resource system with unknown dead zones

Meng, Duo

doi:10.1016/j.neucom.2014.10.034

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…In recent years, some results of synchronization for CNS with unknown parameters have been obtained. In [50], the adaptive synchronization was studied for the response system contains unknown uncertain nonlinearities and unknown dead zones in neural networks. In [51], based on the invariant principle of functional differential equations and parameter identification, the rigorous adaptive feedback scheme is derived to achieve synchronization of two coupled neural networks with timevarying delay.…”

Section: Introductionmentioning

confidence: 99%

Fixed‐Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control

Gong

et al. 2021

Complexity

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This article is related to the issue of fixed-time synchronization of different dimensional complex network systems with unknown parameters. Two suitable adaptive controllers and dynamic parameter estimations are proposed such that the complex network driving and response systems can be synchronized in the settling time. Based on fixed-time control theory and Lyapunov functional method, novel sufficient conditions are provided to guarantee the synchronization within the fixed times, and the settling times are explicitly evaluated, which are independent of the initial synchronization errors. Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms.

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Section: Introductionmentioning

confidence: 99%

Fixed‐Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control

Gong

et al. 2021

Complexity

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“…Many researchers employed many methods to improve the performances of control systems with dead-zone inputs. The most common approaches are adaptive schemes [3][4][5][6], fuzzy systems [7][8][9][10][11][12][13][14], neural networks [15][16][17][18], and sliding mode control [19][20][21][22]. In order to compensate the negative effects of the dead-zone nonlinearity, an inverse dead-zone as a method is used.…”

Section: Introductionmentioning

confidence: 99%

“…Wu et al [5] introduced a smooth inverse of the dead-zone to compensate the effect of the dead-zone in controllers design and proposed an adaptive sliding mode control law to achieve spacecraft attitude tracking problem. By using a four-dimensional energy resource demand supply system, an adaptive neural networks control approach is presented in [17]. The approach not only makes the states of two chaotic systems asymptotic synchronization but also achieved better control performances.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Adaptive Prescribed Performance Control for a Class of Uncertain Nonlinear Systems with Unknown Dead‐Zone Inputs

Xiang

Sun

2017

Mathematical Problems in Engineering

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This paper proposes a fuzzy adaptive prescribed performance control scheme for a class of uncertain chaotic systems with unknown control gains and unknown dead-zone inputs. Firstly, an error transformation is introduced to transform the original constrained system into an equivalent unconstrained one. Then, based on the error transformation technique and the predefined performance technique, a fuzzy adaptive feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded. Finally, an illustrative example is given to demonstrate the effectiveness and usefulness of the proposed technique.

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“…Chaos synchronization has attracted a lot of interest due to its wide engineering application in various areas like secure communication [1][2][3][4], neural networks [5,6], electronic engineering [7], and so on [8,9]. Consider the fact that chaotic system is a class of nonlinear dynamical system which sensitively depends on initial conditions.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Output Feedback Control Scheme for Chaos Synchronization with Input Nonlinearity

Zhao

Zhang

et al. 2016

Journal of Control Science and Engineering

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This paper proposes a robust adaptive output feedback control strategy which can automatically regulate control gain for chaos synchronization. Chaotic systems with input nonlinearities, delayed nonlinear coupling, and external disturbance can achieve synchronization by applying this strategy. Utilizing Lyapunov method and LMI technique, the conditions ensuring chaos synchronization are obtained. Finally, simulations are given to show the effectiveness of our control strategy.

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Neural networks adaptive synchronization for four-dimension energy resource system with unknown dead zones

Cited by 10 publications

References 14 publications

Fixed‐Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control

Fixed‐Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control

Fuzzy Adaptive Prescribed Performance Control for a Class of Uncertain Nonlinear Systems with Unknown Dead‐Zone Inputs

Robust Adaptive Output Feedback Control Scheme for Chaos Synchronization with Input Nonlinearity

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