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Decentralized Adaptive Event-Triggered H∞ Filtering for a Class of Networked Nonlinear Interconnected Systems
IEEE Transactions on Cybernetics
|July 12, 2018
Summary
This study introduces an adaptive event-triggered filtering scheme for networked nonlinear systems. It reduces data transmission by adapting data release rates, improving network bandwidth efficiency and ensuring system stability.
Area of Science:
- Control Systems Engineering
- Networked Systems
- Nonlinear Dynamics
Background:
- Decentralized filtering is crucial for networked nonlinear interconnected systems.
- Network bandwidth limitations pose challenges for data transmission in these systems.
Purpose of the Study:
- To design an adaptive event-triggered scheme for decentralized filtering.
- To alleviate network bandwidth limitations by optimizing data transmission.
Main Methods:
- A novel adaptive event-triggered condition is proposed using an adaptive law for the threshold.
- The threshold adapts based on the error between current and latest state-sampling instants.
- Sufficient conditions for asymptotic stability with disturbance attenuation are derived.
Main Results:
- The adaptive data-transmitting scheme effectively reduces the data release rate.
- Unnecessary data packets are dropped before network access, conserving bandwidth.
- The filtering error system achieves asymptotic stability with a specified disturbance attenuation level.
Conclusions:
- The proposed adaptive event-triggered scheme enhances efficiency in networked nonlinear systems.
- The method successfully balances system performance with network resource constraints.
- The effectiveness is validated through a practical example.
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