SUBSPACE IDENTIFICATION OF PERIODICALLY SWITCHING HAMMERSTEIN-WIENER MODELS FOR MAGNETOSPHERIC DYNAMICS1

Two existing Hammerstein-Wiener identification algorithms and a third novel Hammerstein-Wiener identification algorithm are considered for application to the magnetospheric system. A modified subspace algorithm that allows missing data points is described and used for identifying periodically switching Hammerstein-Wiener models, to capture the periodically time-varying nature of the system. These models are used to predict ground-based magnetometer response using the ACE satellite measurements.