Abstract
In this paper, an event-triggered communication strategy and a distributed filtering scheme are designed for discrete-time nonlinear stochastic systems over wireless sensor networks (WSNs). The underlying system is represented by the Takagi-Sugeno (T-S) fuzzy model, and in addition by the description of the WSN under consideration. The structure of the WSN is established on a deterministic one. Based on an event-triggering condition tailored for each sensor, distributed fuzzy filters are established using the triggered measurements of the smart sensors. As a result, an augmented stochastic system is presented for the distributed filtering design. A robust mean-square asymptotic stability criterion is explored using the Lyapunov stability theory and the Disk stability constraint is applied to improve the performance of the distributed filters. An optimization solution to obtaining the parameters of the distributed filters is developed. Subsequently, a computer-simulated example helps to illustrate the validity of the proposed new filtering design techniques.
| Original language | English |
|---|---|
| Journal | International Journal of Control, Automation and Systems |
| DOIs | |
| Publication status | Published - 2019 Jan 1 |
Fingerprint
Keywords
- Distributed filtering
- event-triggered control
- fuzzy systems
- sensor networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
Cite this
Event-based Distributed Filtering Approach to Nonlinear Stochastic Systems over Sensor Networks. / Hu, Zhongrui; Shi, Peng; Wu, Ligang; Ahn, Choon Ki.
In: International Journal of Control, Automation and Systems, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Event-based Distributed Filtering Approach to Nonlinear Stochastic Systems over Sensor Networks
AU - Hu, Zhongrui
AU - Shi, Peng
AU - Wu, Ligang
AU - Ahn, Choon Ki
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In this paper, an event-triggered communication strategy and a distributed filtering scheme are designed for discrete-time nonlinear stochastic systems over wireless sensor networks (WSNs). The underlying system is represented by the Takagi-Sugeno (T-S) fuzzy model, and in addition by the description of the WSN under consideration. The structure of the WSN is established on a deterministic one. Based on an event-triggering condition tailored for each sensor, distributed fuzzy filters are established using the triggered measurements of the smart sensors. As a result, an augmented stochastic system is presented for the distributed filtering design. A robust mean-square asymptotic stability criterion is explored using the Lyapunov stability theory and the Disk stability constraint is applied to improve the performance of the distributed filters. An optimization solution to obtaining the parameters of the distributed filters is developed. Subsequently, a computer-simulated example helps to illustrate the validity of the proposed new filtering design techniques.
AB - In this paper, an event-triggered communication strategy and a distributed filtering scheme are designed for discrete-time nonlinear stochastic systems over wireless sensor networks (WSNs). The underlying system is represented by the Takagi-Sugeno (T-S) fuzzy model, and in addition by the description of the WSN under consideration. The structure of the WSN is established on a deterministic one. Based on an event-triggering condition tailored for each sensor, distributed fuzzy filters are established using the triggered measurements of the smart sensors. As a result, an augmented stochastic system is presented for the distributed filtering design. A robust mean-square asymptotic stability criterion is explored using the Lyapunov stability theory and the Disk stability constraint is applied to improve the performance of the distributed filters. An optimization solution to obtaining the parameters of the distributed filters is developed. Subsequently, a computer-simulated example helps to illustrate the validity of the proposed new filtering design techniques.
KW - Distributed filtering
KW - event-triggered control
KW - fuzzy systems
KW - sensor networks
UR - http://www.scopus.com/inward/record.url?scp=85062897487&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062897487&partnerID=8YFLogxK
U2 - 10.1007/s12555-018-0629-1
DO - 10.1007/s12555-018-0629-1
M3 - Article
AN - SCOPUS:85062897487
JO - International Journal of Control, Automation and Systems
JF - International Journal of Control, Automation and Systems
SN - 1598-6446
ER -