Mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks

Muralisankar, S.; Manivannan, A.; Balasubramaniam, P.

doi:10.1016/j.isatra.2015.03.004

Cited by 19 publications

(1 citation statement)

References 27 publications

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“…In Peng et al (2009) and Bao and Cao (2011), by introducing a Bernoulli variable, the systems with distribution-dependent random delays can be formulated as unified models with randomly occurring delays. This approach has been applied to stability analysis, estimation/filtering and control for systems with random delay with known probabilistic distribution (Bao & Cao, 2011;Muralisankar et al, 2015;Sheng et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

Chen

et al. 2020

International Journal of Systems Science

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This paper focuses on the passive control problem for Markov jump systems with piecewise-constant transition rates, random nonlinearities and random communication delays. An observer is used to obtain the system state, and communication delay with probabilistic distribution is considered. The probabilistic properties of the nonlinear perturbations and communication delays are described by two mutually independent Bernoulli sequences. Based on average dwell time method and Lyapunov stability theory, a sufficient stochastic passivity condition is presented. By singular value decomposition technique the gain matrices can be computed via strict linear matrix inequalities, and the desired controller guarantees the stochastic passivity of the closed-loop augmented system. The effectiveness of the method is illustrated by a numerical example.

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Section: Introductionmentioning

confidence: 99%

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

Chen

et al. 2020

International Journal of Systems Science

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Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks

Zhu

Jiang

Pan

2022

Adaptive Control & Signal

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This article investigates the fault detection problem in finite-frequency domain for a class of nonlinear networked systems under stochastic cyber-attacks.A novel adaptive event-triggered scheme is introduced to mitigate the transmission burden of the network. A unified measurement model is proposed to take the randomly occurring cyber-attacks and the transmission delays into account simultaneously. Under the consideration of fault sensitivity and disturbance robustness, the addressed fault detection problem is converted into an auxiliary H − ∕H ∞ filtering problem by properly augmenting the states of the original system and the fault detection filter. Intensive stochastic analysis is carried out to obtain sufficient conditions for the existence of the desired fault detection filter, and the corresponding optimal filter parameters can be easily derived by solving a convex optimization problem. Finally, an illustrative example is presented to show the effectiveness and applicability of the proposed method.

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Non-fragile asynchronous H ∞ control for uncertain stochastic memory systems with Bernoulli distribution

Luo

Tian

Zhong

et al. 2017

Applied Mathematics and Computation

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Mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks

Cited by 19 publications

References 27 publications

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks

Non-fragile asynchronous H ∞ control for uncertain stochastic memory systems with Bernoulli distribution

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