The problem of Linear Multivariable State Space model identification from input-output data can under the presence of process-and measurement noise be solved in a non-iterative way when incorporating instrumental variables constructed from both input and output sequences in the recently developed cl
โฆ LIBER โฆ
Choice of state-space basis in combined deterministic-stochastic subspace identification
โ Scribed by Peter Van Overschee; Bart De Moor
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 680 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0005-1098
No coin nor oath required. For personal study only.
โฆ Synopsis
paper describes how the state-space basis of models identified with subspace identification algorithms can be determined. It is shown that this basis is determined by the input spectrum and by user-defined input and output weightings. Through the connections between subspace identification and frequency-weighted balancing, the statespace basis of the subspace-identified models is shown to coincide with a frequency-weighted balanced basis.
๐ SIMILAR VOLUMES
Identification of the deterministic part
โ
Michel Verhaegen
๐
Article
๐
1994
๐
Elsevier Science
๐
English
โ 1018 KB