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Dynamic Event-Triggered Predictive Control for Interval Type-2 Fuzzy Systems with Imperfect Premise Matching.
Jingfeng Zhou1, Jianming Cao1, Jing Chen1
1School of Science, Jiangnan University, Wuxi 214122, China.
Entropy (Basel, Switzerland)
|November 27, 2021
Summary
This study introduces dynamic event-triggered predictive control for interval type-2 (IT2) fuzzy systems. The method enhances network efficiency and ensures system stability despite communication unreliability.
Area of Science:
- Control Systems Engineering
- Fuzzy Logic Systems
- Networked Control Systems
Background:
- Interval Type-2 (IT2) fuzzy systems are complex and require robust control strategies.
- Dynamic event-triggered mechanisms are crucial for conserving network resources in control systems.
- Imperfect premise matching poses challenges in fuzzy system control design.
Purpose of the Study:
- To investigate the dynamic event-triggered predictive control problem for IT2 fuzzy systems.
- To develop a control strategy that addresses imperfect premise matching and unreliable communication.
- To enhance the efficiency of data transmission and ensure system stability.
Main Methods:
- Proposed an IT2 fuzzy systems model incorporating a dynamic event-triggered mechanism.
- Designed a predictive controller to handle system state prediction between transmissions.
- Utilized Lyapunov stability theory and imperfect premise matching for analysis.
Main Results:
- Derived sufficient conditions for system stabilization.
- Obtained the controller gain for the proposed control strategy.
- Demonstrated the effectiveness of the method through numerical examples.
Conclusions:
- The proposed dynamic event-triggered predictive control is effective for IT2 fuzzy systems.
- The method conserves network resources while maintaining system stability.
- The approach is validated for systems with imperfect premise matching and unreliable networks.
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