Name
Title | ||
|---|---|---|
Adaptive filtering based collaborative actuation for wireless sensor and actuator networks. |
Abstract | ||
|---|---|---|
Wireless sensor and actuator networks WSANs are emerging as a new generation of sensor networks. To accomplish effective sensing and acting tasks, efficient coordinate mechanisms among the nodes are desirable. As an attempt in this direction, this paper develops a collaborative estimation and control mechanism, which addresses the nodes coordination in a distributed manner. First, we discuss the system model and system partition that are used to construct the distributed architecture. Then, a collaborative estimation and control scheme is proposed to coordinate sensor and actuator nodes. This scheme includes two components, namely recursive least squares based federated Kalman filter RLS-FKF and PID neural network PIDNN. It schedules the corresponding nodes based on the characteristics of current events, deals with data fusion and system estimation problems through RLS-FKF, and utilises PIDNN controller to improve system transient and steady-state responses. Simulations demonstrate the effectiveness of proposed methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1504/IJAHUC.2015.073435 | IJAHUC |
Keywords | Field | DocType |
WSANs, wireless sensor and actuator networks, recursive least squares, federated Kalman filter, PID neural network | Key distribution in wireless sensor networks,Control theory,Computer science,Computer network,Kalman filter,Sensor fusion,Wireless sensor network,Recursive least squares filter,System model,Actuator,Distributed computing | Journal |
Volume | Issue | ISSN |
20 | 4 | 1743-8225 |
Citations | PageRank | References |
3 | 0.40 | 9 |
Authors | ||
2 | ||