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Adaptive filtering based collaborative actuation for wireless sensor and actuator networks

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.