Authors: Lei Mo; Bugong Xu
Addresses: State Key Lab. of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China; Key Lab. of Autonomous Systems and Network Control, Ministry of Education, College of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China ' Key Lab. of Autonomous Systems and Network Control, Ministry of Education, College of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
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.
Keywords: 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.
International Journal of Ad Hoc and Ubiquitous Computing, 2015 Vol.20 No.4, pp.223 - 236
Received: 18 Apr 2013
Accepted: 20 Jan 2014
Published online: 08 Dec 2015 *