In this study, the authors present an overview of closed‐loop subspace identification
methods found in the recent literature. Since a significant number of algorithms has …

Subspace methods have emerged as useful tools for the identification of linear time invariant
discrete time systems. Most of the methods have been developed for the open loop case to …

Subspace identification for closed loop systems has been recently studied by several
authors. A class of new and consistent closed-loop subspace algorithms is based on …

In time-domain subspace methods for identifying linear-time invariant dynamical systems,
the model matrices are typically estimated from least squares, based on estimated Kalman …

We give a general overview of the state of the art in subspace system identification methods.
We have restricted ourselves to the most important ideas and developments since the …

Subspace identification methods (SIMs) for estimating state-space models have been
proven to be very useful and numerically efficient. They exist in several variants, but all have …

In this paper we present a new identification method that points at the close relationship
between high order ARX modeling and subspace identification. A high order ARX model is …

This study deals with the problem of continuous-time model identification and presents two
subspace-based algorithms capable of dealing with data generated by systems operating in …

In the literature results can be found which claim consistency for the subspace method under
certain quite weak assumptions. Unfortunately, a new result gives a counter example …

Subspace-based methods for system identification have attracted much attention during the
past few years. This interest is due to the ability of providing accurate state-space models for …