Recursive Subspace Prediction of Linear Time-varying Stochastic Systems

Authors:	Akira Ohsumi, Kyoto Institute of Technology, Japan Kameyama Kentaro, Kyoto Institute of Technology, Japan
Topic:	1.1 Modelling, Identification & Signal Processing
Session:	Subspace Methods
Keywords:	Subspace prediction; subspace methods; subspace identification; recursive algorithm;time-varying systems

Abstract

In this paper, a new subspace method for predicting time-invariant/varying stochastic systems is investigated in the 4SID framework. Using theconcept of angle between past and current subspaces spanned by the extendedobservability matrices, the future subspace is predicted by rotating currentsubspace in the geometrical sense. In order to treat even time-varying system,a recursive algorithm is derived for implementation. The proposed algorithm istested by simulation experiments.