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A typical design procedure for model predictive control or control performance monitoring
consists of: identification of a parametric or nonparametric model; derivation of the output …

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 methods for identification of linear time-invariant dynamical systems typically
consist of two main steps. First, a so-called subspace estimate is constructed. This first step …

Subspace-based state-space system identification (4SID) methods have recently been
proposed as an alternative to more traditional techniques for multivariable system …

The paper focuses on the time domain output-only technique called Data-Driven Stochastic
Subspace Identification (DD-SSI); in order to identify modal models (frequencies, dam** …

System identification is a key discipline within the field of automation that deals with inferring
mathematical models of dynamic systems based on input-output measurements …

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 …

An important step in the operational modal analysis of a structure is to infer on its dynamic
behavior through its modal parameters. They can be estimated by various modal …

The MOESP type of subspace algorithms are used for the identification of linear, discrete
time, finite-dimensional state-space systems. They are based on the geometric structure of …