Subspace identification for non-linear systems with measured-input non-linearities
From MaRDI portal
Publication:5704586
DOI10.1080/00207170500214095zbMath1086.93011OpenAlexW2086400417MaRDI QIDQ5704586
Seth L. Lacy, Dennis S. Bernstein
Publication date: 15 November 2005
Published in: International Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207170500214095
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (4)
A new frequency-domain subspace algorithm with restricted poles location through LMI regions and its application to a wind tunnel test ⋮ A nonlinear subspace-prediction error method for identification of nonlinear vibrating structures ⋮ A subspace algorithm for simultaneous identification and input reconstruction ⋮ Identification of cascade systems with backlash
Cites Work
- Unnamed Item
- Statistical analysis of novel subspace identification methods
- Subspace identification from closed loop data
- Identifying MIMO Wiener systems using subspace model identification methods
- A new algorithm for the identification of multiple input Wiener systems
- On consistency of subspace methods for system identification
- Consistency and asymptotic normality of some subspace algorithms for systems without observed inputs
- 4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems
- Parameter identification of discontinuous Hammerstein systems
- Fast approximate identification of nonlinear systems
- Consistency analysis of subspace identification methods based on a linear regression approach
- Some facts about the choice of the weighting matrices in Larimore type of subspace algorithms
- A class of subspace model identification algorithms to identify periodically and arbitrarily time-varying systems
- Subspace-based methods for the identification of linear time-invariant systems
- Consistency and relative efficiency of subspace methods
- Analysis of the asymptotic properties of the MOESP type of subspace algorithms
- Stochastic theory of continuous-time state-space identification
- Subspace model identification Part 3. Analysis of the ordinary output-error state-space model identification algorithm
- Nonparametric identification of Hammerstein systems
- Nonparametric identification of Wiener systems
- Convergence analysis of recursive identification algorithms based on the nonlinear Wiener model
- Identification of FIR Wiener systems with unknown, non-invertible, polynomial non-linearities
- Identification of stable models in subspace identification by using regularization
- Identifying MIMO Hammerstein systems in the context of subspace model identification methods
- Subspace identification with guaranteed stability using constrained optimization
- Recursive subspace identification of linear and nonlinear Wiener state-space models
- Order estimation for subspace methods
- Parameter identification of Wiener systems with discontinuous nonlinearities
This page was built for publication: Subspace identification for non-linear systems with measured-input non-linearities