System Identification using LQG-Balanced Model Reduction,
System identification of linear multivariable dy-namic models based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.
