Aperiodic Sampled-Data-Based Control for Interval Type-2 Fuzzy Systems via Refined Adaptive Event-Triggered Communication Scheme

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Zhichen Li ◽  
Huaicheng Yan ◽  
Hao Zhang ◽  
Hak-Keung Lam ◽  
Meng Wang
Keyword(s):  
Fuzzy Systems ◽  
Sampled Data ◽  
Communication Scheme ◽  
Interval Type ◽  
Event Triggered

scholarly journals Event-Triggered Mixed Non-Fragile and Measurement Quantization Filtering Design for Interval Type-2 Fuzzy Systems

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 1533-1545
Author(s):  
Chunsong Han ◽  
Dingding Song ◽  
Guangtao Ran ◽  
Jiafeng Yu
Keyword(s):  
Fuzzy Systems ◽  
Interval Type ◽  
Event Triggered

scholarly journals Dynamic Event-Triggered Predictive Control for Interval Type-2 Fuzzy Systems with Imperfect Premise Matching

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1452
Author(s):  
Jingfeng Zhou ◽  
Jianming Cao ◽  
Jing Chen ◽  
Aihua Hu ◽  
Jingxiang Zhang ◽  
...  
Keyword(s):  
Communication Networks ◽  
Predictive Control ◽  
Fuzzy Systems ◽  
Sufficient Conditions ◽  
Dynamic Event ◽  
Systems Model ◽  
Interval Type ◽  
Imperfect Premise Matching ◽  
Event Triggered

This paper investigates the dynamic event-triggered predictive control problem of interval type-2 (IT2) fuzzy systems with imperfect premise matching. First, an IT2 fuzzy systems model is proposed, including a dynamic event-triggered mechanism, which can save limited network resources by reducing the number of data packets transmitted, and a predictive controller, which can predict the state of the system between the two successful transmitted instants to deal with unreliable communication networks. Then, according to the Lyapunov stability theory and imperfect premise matching method, sufficient conditions for system stabilization and the controller gain are obtained. Finally, the validity of the proposed method is demonstrated by the numerical examples.

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