Adaptive filtering based collaborative actuation for wireless sensor and actuator networks. (2015)

• Record Type: Journal Article
• Authors: Mo, Lei; Xu, Bugong
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 20:Number 4(2015)
• Page Start: 223
• Page End: 236
• Publication Date: 2015
• Subjects: WSANs -- wireless sensor and actuator networks -- recursive least squares -- RLS -- federated Kalman filter -- PID neural networks -- adaptive filtering -- collaborative actuation -- wireless sensor networks -- WSNs -- data fusion -- system estimation -- simulation; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

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.