Dynamic event-based non-fragile state estimation for complex networks via partial nodes information
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Publication:2068253
DOI10.1016/j.jfranklin.2021.10.038zbMath1480.93415OpenAlexW3210466991MaRDI QIDQ2068253
Luyang Yu, Wenbing Zhang, Yurong Liu, Ying Cui, Fawaz E. Alsaadi
Publication date: 19 January 2022
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.10.038
Estimation and detection in stochastic control theory (93E10) Discrete event control/observation systems (93C65) Delay control/observation systems (93C43) Networked control (93B70)
Related Items (3)
Non-fragile PD control of linear time-delay positive discrete-time systems ⋮ Learning-based non-fragile state estimation for switching complex dynamical networks ⋮ A brief survey on nonlinear control using adaptive dynamic programming under engineering-oriented complexities
Cites Work
- Recursive state estimation based-on the outputs of partial nodes for discrete-time stochastic complex networks with switched topology
- Augmented Lagrange algorithms for distributed optimization over multi-agent networks via edge-based method
- Dynamic event-triggered mechanism for \(H_\infty\) non-fragile state estimation of complex networks under randomly occurring sensor saturations
- Non-fragile state estimation for delayed fractional-order memristive neural networks
- Event-triggered robust state estimation for systems with unknown exogenous inputs
- Dynamic Triggering Mechanisms for Event-Triggered Control
- Synchronization in Complex Networks With Stochastically Switching Coupling Structures
- Distributed Learning Over Networks: Effect of Using Historical Observations
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