Subspace identification for continuous-time stochastic systems via distribution-based approach

Authors:
Akira Ohsumi;Kentaro Kameyama;Ken-Ichi Yamaguchi
Affiliations:
Department of Mechanical & System Engineering, Graduate School of Engineering and Science, Kyoto Institute of Technology, Matsugasaki, Sakyo, Kyoto 606-8585, Japan;Department of Mechanical & System Engineering, Graduate School of Engineering and Science, Kyoto Institute of Technology, Matsugasaki, Sakyo, Kyoto 606-8585, Japan;Department of Mechanical & System Engineering, Graduate School of Engineering and Science, Kyoto Institute of Technology, Matsugasaki, Sakyo, Kyoto 606-8585, Japan
Venue:
Automatica (Journal of IFAC)
Year:
2002

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Abstract

This paper presents a novel approach for system identification of continuous-time stochastic state space models from random input-output continuous data. The approach is based on the introduction of random distribution theory in describing (higher) time derivatives of stochastic processes, and the input-output algebraic relationship is derived which is treated in the time-domain. The efficacy of the approach is examined by comparing with other approaches employing the filters.