Subspace-based prediction of linear time-varying stochastic systems

Authors:
Kentaro Kameyama;Akira Ohsumi
Affiliations:
Department of Mechanical Engineering, Fukui National College of Technology, Geshi, Sabae, Fukui 9168507, Japan;Department of Mechanical & System Engineering, Graduate School of Science and Technology, Kyoto Institute of Technology, Matsugasaki, Sakyo, Kyoto 6068585, Japan
Venue:
Automatica (Journal of IFAC)
Year:
2007

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Abstract

In this paper, a new subspace method for predicting time-varying stochastic systems is proposed. Using the concept of angle between past and present subspaces spanned by the extended observability matrices, the future signal subspace is predicted by rotating the present subspace in the geometrical sense, and time-varying system matrices are derived from the resultant signal subspace. Proposed algorithm is improved for fast-varying systems. Furthermore, recursive implementation of both algorithms is developed.