Exponential stability of nonlinear time-delay systems with delayed impulse effects

Chen, Wu‐Hua; Zheng, Wei Xing

doi:10.1016/j.automatica.2011.02.031

Cited by 205 publications

(88 citation statements)

References 18 publications

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“…(4), we can see that the synchronization of discrete-time complex networks under delayed impulsive control is transformed into the stabilization problem of discrete-time systems with delayed impulses. Recently, delayed impulsive effects have considered in stability and synchronization problems of various impulsive continuous-time systems [2][3][4]34,40]. It should be mentioned that a delayed impulsive control strategy has been proposed to guarantee the synchronization of continuous-time complex networks in [40], which can generalize several impulsive control strategies, e.g., [2,8,35,36].…”

Section: Model Description and Some Preliminariesmentioning

confidence: 99%

“…Therefore, it is of great importance to take into account impulsive input delays when using impulsive control strategy. Recently, impulsive input delays have been considered in continuous-time impulsive systems [3,4,34]. Based on these results, delayed impulsive control strategies, which are more general than the general impulsive control, have been proposed in [2,40].…”

Section: Introductionmentioning

confidence: 99%

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Delayed impulsive synchronization of discrete-time complex networks with distributed delays

Fang

Zhang

et al. 2015

Nonlinear Dyn

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In this paper, a novel delayed impulsive control strategy is proposed for synchronization of discrete-time complex networks with distributed delays. Different from the existing results, the involving time delays include distributed delays and impulsive input delays. Employing the Razumikhin theorem and the mathematical induction method, several sufficient criteria are derived in terms of algebraic conditions, which depend on impulsive input delays and impulsive control gains. Meanwhile, the derived criteria also reveal the relationship between the bounds of impulsive intervals and impulsive input delays. Finally, two examples are given to illustrate the effectiveness of the proposed approach.

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Section: Model Description and Some Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Delayed impulsive synchronization of discrete-time complex networks with distributed delays

Fang

Zhang

et al. 2015

Nonlinear Dyn

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“…In recent years, the theory of impulsive differential systems has been applied to many aspects including of stability analysis, control design and synchronization, etc. A large amount of results on impulsive systems have appeared in the literature, see [2,5,8,18,22].…”

Section: Introductionmentioning

confidence: 99%

Stability of impulsive differential systems with state-dependent impulses via the linear decomposition method

Hu¹,

Sui²,

Akça³

et al. 2017

J. Nonlinear Sci. Appl.

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In this paper, we discuss the stability problem of the impulsive differential systems with state-dependent impulses. By using the linear decomposition methods, some sufficient conditions ensuring stability of the impulsive differential systems with state-dependent impulses are obtained and the estimate of the solution of such nonlinear systems is also acquired. Our results improve and generalize some of the known results given in earlier references. An example is given to demonstrate our results.

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“…Since nonlinearities may cause undesirable dynamic behaviors such as oscillation or even instability, the analysis and synthesis problems for nonlinear systems have long been the main stream of research topics and much effort has been made to deal with the nonlinear stochastic systems, see e.g. [2,4,14,19,33]. It is worth pointing out that, in most literature, the nonlinearities are assumed to occur in a deterministic way.…”

Section: Introductionmentioning

confidence: 99%

Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

et al. 2012

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In this paper, the extended Kalman filtering problem is investigated for a class of nonlinear systems with multiple missing measurements over a finite horizon. Both deterministic and stochastic nonlinearities are included in the system model, where the stochastic nonlinearities are described by statistical means that could reflect the multiplicative stochastic disturbances. The phenomenon of measurement missing occurs in a random way and the missing probability for each sensor is governed by an individual random variable satisfying a certain probability distribution over the interval [0,1]. Such a probability distribution is allowed to be any commonly used distribution over the interval [0, 1] with known conditional probability. The aim of the addressed filtering problem is to design a filter such that, in the presence of both the stochastic nonlinearities and multiple missing measurements, there exists an upper bound for the filtering error covariance. Subsequently, such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations that are of a form suitable for recursive computation in online applications. An illustrative example is given to demonstrate the effectiveness of the proposed filter design scheme.

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Exponential stability of nonlinear time-delay systems with delayed impulse effects

Cited by 205 publications

References 18 publications

Delayed impulsive synchronization of discrete-time complex networks with distributed delays

Delayed impulsive synchronization of discrete-time complex networks with distributed delays

Stability of impulsive differential systems with state-dependent impulses via the linear decomposition method

Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

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