Extended dissipativity state estimation for switched discrete-time complex dynamical networks with multiple communication channels: A sojourn probability dependent approach

Sasirekha, R.; Rakkiyappan, R.

doi:10.1016/j.neucom.2017.04.063

Cited by 10 publications

(9 citation statements)

References 18 publications

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“…In CN applications, an underlying assumption is that the coupling strengths among CN nodes can be described as certain known constants, see e.g. [30], [35], [40], [45]. This assumption is, unfortunately, quite restrictive in practice.…”

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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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%

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 the practical environments, the connection relationship might change randomly due to the dynamical interaction situations among the spatially distributed network nodes, where the related examples can be found in the virus spreading networks and wireless sensor networks [19,20]. That is to say, the topology of the entire network switches in a random manner, and hence it inevitably induces the difficulties and complexities of analysing the time-varying complex dynamical networks [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Resilient state estimation for time‐varying uncertain dynamical networks with data packet dropouts and switching topology: an event‐triggered method

Gao

Chen

et al. 2020

IET Control Theory & Applications

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“…Thus, investigating the state estimation problem for complex networks is crucial. Until now, complex networks studies have mainly focussed on synchronization phenomenon and state estimation (Sasirekha & Rakkiyappan, 2017). For instance, Lv, Liang, and Cao (2011) has studied the neural network state estimation under noise disturbance.…”

Section: Introductionmentioning

confidence: 99%

Fault estimation for complex networks with model uncertainty and stochastic communication protocol

Zhang

Liu

2019

Systems Science & Control Engineering

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This paper aims to investigate the fault estimation problem for a class of complex networks with model uncertainty and stochastic communication protocol. The model uncertainty existing in the system is norm-bounded. Stochastic communication protocol is employed to cope with possible data collisions in the multiple signal transmissions. An augmented system is constructed by forming an augmented state vector consisting of system states and related faults. By designing the state estimator, the state estimation problem, in the presence of model uncertainty and random disturbance is solved. The parameters of the estimator are obtained by solving several recursive matrix equations such that an upper bound of the estimation error covariance is established and it is minimized. Finally, we give a simulation example to verify the feasibility of the proposed state estimation scheme.

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Extended dissipativity state estimation for switched discrete-time complex dynamical networks with multiple communication channels: A sojourn probability dependent approach

Cited by 10 publications

References 18 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

Resilient state estimation for time‐varying uncertain dynamical networks with data packet dropouts and switching topology: an event‐triggered method

Fault estimation for complex networks with model uncertainty and stochastic communication protocol

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