System identification: theory for the user
System identification: theory for the user
System identification
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Subspace-based methods for the identification of linear time-invariant systems
Automatica (Journal of IFAC) - Special issue on trends in system identification
A unifying theorem for three subspace system identification algorithms
Automatica (Journal of IFAC) - Special issue on trends in system identification
Choice of state-space basis in combined deterministic-stochastic subspace identification
Automatica (Journal of IFAC) - Special issue on trends in system identification
A linear regression approach to state-space subspace system identification
Signal Processing - Special issue: subspace methods, part II: system identification
Statistical analysis of novel subspace identification methods
Signal Processing - Special issue: subspace methods, part II: system identification
Automatica (Journal of IFAC)
Comparison of some instrumental variable methods-Consistency and accuracy aspects
Automatica (Journal of IFAC)
On behavioral model identification
Signal Processing
Automatica (Journal of IFAC)
Subspace identification of MIMO LPV systems using a periodic scheduling sequence
Automatica (Journal of IFAC)
Computers and Electronics in Agriculture
Some facts about the choice of the weighting matrices in Larimore type of subspace algorithms
Automatica (Journal of IFAC)
Brief Subspace identification using instrumental variable techniques
Automatica (Journal of IFAC)
Subspace-based system identification: weighting and pre-filtering of instruments
Automatica (Journal of IFAC)
Analysis of the asymptotic properties of the MOESP type of subspace algorithms
Automatica (Journal of IFAC)
Brief Consistency analysis of subspace identification methods based on a linear regression approach
Automatica (Journal of IFAC)
Brief Recursive 4SID algorithms using gradient type subspace tracking
Automatica (Journal of IFAC)
Subspace identification for continuous-time stochastic systems via distribution-based approach
Automatica (Journal of IFAC)
Subspace identification by data orthogonalization and model decoupling
Automatica (Journal of IFAC)
Brief Subspace identification of closed loop systems by the orthogonal decomposition method
Automatica (Journal of IFAC)
A novel subspace identification approach with enforced causal models
Automatica (Journal of IFAC)
Identification methods in a unified framework
Automatica (Journal of IFAC)
Asymptotic properties of subspace estimators
Automatica (Journal of IFAC)
On the ill-conditioning of subspace identification with inputs
Automatica (Journal of IFAC)
| Hi-index | 22.18 |
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 usually consists of estimating the range space of the extended observability matrix. Secondly, an estimate of system parametersis obtained, based on the subspace estimate. In this paper, the consistency of a large class of methods for estimating the extended observability matrix is analyzed. Persistence of excitation conditions on the input signal are given which guarantee consistent estimates for systems with only measurement noise. For systems with process noise, it is shown that a persistence of excitation condition on the input is not sufficient. More precisely, an example for which the subspace methods fail to give a consistent estimate of the transfer function is given. This failure occurs even if the input is persistently exciting of any order. It is also shown that this problem can be eliminated if stronger conditions on the input signal are imposed.