Sampled-data state estimation for a class of delayed complex networks via intermittent transmission

Cui, Ying; Liu, Yurong; Zhang, Wenbing; Hayat, Tasawar; Alsaedi, Ahmed

doi:10.1016/j.neucom.2017.04.031

Cited by 16 publications

(4 citation statements)

References 32 publications

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“…Up to now, plenty of filtering/estimation algorithms have been devised for a great variety of CNs (see [5], [18], [27], [45], [48], [50]) with tremendous attention from both academia and industry. In practical engineering, many complex systems have time-varying parameters that might be caused by different reasons, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…operating point shifting and parameter fluctuation [1], [2]. To address the filtering issues of time-varying CNs, various methods have been devised with examples including the finite-horizon H ∞ filtering and recursive filtering (RF) algorithms, where the latter is most widely studied algorithm that has gained a great deal of research interest [5], [10], [15], [20]- [24].…”

Section: Introductionmentioning

confidence: 99%

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Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks

Gao

Dong

Wang

et al. 2022

IEEE Trans. Cybern.

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In this paper, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may suffer from deception attacks which are governed by Bernoulli-distributed random variables. The purpose of the problem under consideration is to design a minimum-variance filter for CNs with deception attacks, state saturations and UCSs such that upper bounds on the resulting error covariances are guaranteed. Then, the expected filter gains are acquired via minimizing the traces of such upper bounds and sufficient conditions are established to ensure the exponential mean-square boundedness of the filtering errors. At last, two simulation examples (including a practical application) are exploited to validate the effectiveness of our designed approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks

Gao

Dong

Wang

et al. 2022

IEEE Trans. Cybern.

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show abstract

“…In [18], each gene expression process can be roughly defined by a continuous dynamic behavior in a gene regulatory network, which is made up of a set of interacting genes, but when the protein concentration exceeds a certain threshold, the regulation kinetics will change abruptly. Furthermore, stable and unstable subsystems usually coexist in complex networks [19][20][21] since some subsystems in a switched system may be unstable due to disturbances, highly nonlinear dynamics, or possible failures [19,22]. As a result, considering switched neural networks (SNNs) with only stable or unstable subsystems are impractical.…”

Section: Introductionmentioning

confidence: 99%

Exponential Stability of Switched Neural Networks with Partial State Reset and Time-Varying Delays

Han

Zhang

2022

Mathematics

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This paper mainly investigates the exponential stability of switched neural networks (SNNs) with partial state reset and time-varying delays, in which partial state reset means that only a fraction of the states can be reset at each switching instant. Moreover, both stable and unstable subsystems are also taken into account and therefore, switched systems under consideration can take several switched systems as special cases. The comparison principle, the Halanay-like inequality, and the time-dependent switched Lyapunov function approach are used to obtain sufficient conditions to ensure that the considered SNNs with delays and partial state reset are exponentially stable. Numerical examples are provided to demonstrate the reliability of the developed results.

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“…instability, degradations and oscillation) [14], [15]. Recently, a large number of literatures were published about the state estimation problems for some complex networks with timedelays, see e. g. [16]- [19]. To mention a few, a robust H ∞ filtering problem was discussed for complex network systems with time-delays and stochastic packet dropouts, where the estimation error exponentially converges to zero in mean square sense and the H ∞ performance was guaranteed [16].…”

Section: Introductionmentioning

confidence: 99%

Optimized State Estimation of Uncertain Linear Time-Varying Complex Networks With Random Sensor Delay Subject to Uncertain Probabilities

2019

IEEE Access

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This paper is concerned with the optimal state estimation problem for a class of time-varying uncertain dynamical networks with mixed time-delay under uncertain probabilities. Here, the mixed timedelays include the constant time-delay and the random sensor delay, where the random sensor delay is depicted by a Bernoulli distributed random variable and the occurrence probability of the random sensor delay can be uncertain. The major novelty of the paper lies in that a new time-varying state estimation algorithm is given such that, for all parameter uncertainties, mixed time-delays and uncertain probabilities, a locally optimal upper bound of the estimation error covariance is obtained and the desirable estimator parameter of easy-to-implement feature is designed. Moreover, the performance evaluation problem of the presented estimation algorithm is solved, where the monotonicity analysis is shown regarding the trace of the upper bound and the deterministic occurrence probability of random sensor delay. At last, the simulations are given to show the validity and correctness of the proposed time-varying estimation method. In particular, the comparisons are given to show the relationship of the upper bound and occurrence probability. INDEX TERMSNetworked systems, time-varying complex networks, optimized state estimation, random sensor delay, uncertain probabilities.

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Sampled-data state estimation for a class of delayed complex networks via intermittent transmission

Cited by 16 publications

References 32 publications

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks

Exponential Stability of Switched Neural Networks with Partial State Reset and Time-Varying Delays

Optimized State Estimation of Uncertain Linear Time-Varying Complex Networks With Random Sensor Delay Subject to Uncertain Probabilities

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