Event Triggered Heterogeneous Nonlinear Filter Considering Nodal Computation Capability

The constraints including both the communication and computation power at sensor nodes are widely encountered in the practical WAMS application. This chapter designs an event triggered heterogeneous nonlinear Kalman filter (ET-HNF). The ET-HNF utilizes the unified filtering of unscented transformation with particle filter theories so that the accuracy and the relief of communication burden can be guaranteed at the same time. An unscented transformation based event triggered UKF (ET-UKF) is firstly designed at the sensor node to supply the event triggered strategy. Furthermore, a Monte Carlo based filtering algorithm is designed in the estimation center to provide the accurate filtering results. The feasibility and performance of the developed filterings are verified based on the IEEE 39 bus system.