Adaptive event-triggered dissipative filtering for interval type-2 fuzzy semi-Markov jump systems with quantization and sensor failures
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Summary
This summary is machine-generated.This study develops an adaptive event-triggered dissipative filter for interval type-2 fuzzy semi-Markov jump systems, reducing communication load and enhancing robustness against sensor failures and disturbances.
Area Of Science
- Control Systems Engineering
- Fuzzy Logic Systems
- Stochastic Systems
Background
- Interval type-2 fuzzy semi-Markov jump systems are susceptible to quantization and sensor failures.
- Existing filtering methods can be conservative and communication-intensive.
Purpose Of The Study
- To design an adaptive event-triggered dissipative filter for interval type-2 fuzzy semi-Markov jump systems.
- To reduce communication burden and improve system resilience.
- To relax the conservativeness of traditional filtering models.
Main Methods
- Utilizing an affine parameter-based membership function to decrease model conservativeness.
- Developing a novel dissipative filtering approach with an asymmetric Lyapunov-Krasovskii functional.
- Applying recent integral inequalities and linear matrix inequality techniques.
- Incorporating an adaptive event-triggered mechanism with network transmission delay.
Main Results
- The proposed filter effectively reduces communication load compared to existing methods.
- Enhanced flexibility in managing sensor failures and external disturbances.
- Stochastic stabilization criteria are derived for simultaneous determination of weighting matrices and filter parameters.
- Validation through two numerical examples, including a tunnel diode circuit.
Conclusions
- The developed affine parameter-based dissipative filtering approach offers significant advantages in terms of communication efficiency and robustness.
- The method provides a flexible and less conservative solution for complex systems.
- The approach is validated by numerical simulations, demonstrating its practical applicability.
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