Tohru Katayama

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This paper is concerned with the identification of a class of piecewise affine systems called a piecewise affine autoregressive exogenous (PWARX) model. The PWARX model is composed of ARX sub-models each of which corresponds to a polyhedral region of the regression space. Under the temporary assumption that the number of sub-models is known a priori, the(More)
A method of identifying closed-loop systems is developed by using the orthogonal decomposition (ORT) method. The idea is to project the input and output data onto the space of exogenous inputs by using the LQ decomposition to obtain their deterministic components. The ORT-based method is then applied to deterministic components like the direct approach in(More)
We develop a closed loop subspace identification method based on stochastic realization theory. Using the preliminary orthogonal decomposition of (Picci and Katayama, 1996b) we show that, under the assumption that the exogenous input is feedback-free and persistently exciting (PE), the identification of closed loop systems is divided into two subproblems:(More)
In this paper, we consider a stochastic realization problem with finite covariance data based on “LQ decomposition” in a Hilbert space, and re-derive a non-stationary finite-interval realization ([4, 5]). We develop a new algorithm of computing system matrices of the finiteinterval realization by LQ decomposition, followed by the SVD of a certain block(More)
In this paper, we consider a problem of identifying the deterministic part of a closed loop system by applying the stochastic realization technique of (Signal Process. 52 (2) (1996) 145) in the framework of the joint input–output approach. Using a preliminary orthogonal decomposition, the problem is reduced to that of identifying the plant and controller(More)