Output details
15 - General Engineering
Brunel University London
Probability-dependent gain-scheduled filtering for stochastic systems with missing measurements
This paper addresses a new filtering problem associated with the time-varying features of missing measurements. This work is being applied to my ongoing EPSRC project (EP/K006487/1) on dynamic state estimation of power systems based on Phasor Measurement Units (PMUs). PMUs are emerging devices that are being deployed in power networks due to their high frequency and accurate measurements (up to 60 measurements per second). However, for economic reasons, it is not affordable to replace all the existing measurement units with PMUs in the foreseeable future. This paper solves the challenging problem of dynamic state estimation with partial PMU measurements