Identification of a weighted combination of multivariable local linear state-space systems from input and output data

Proceedings of the IEEE Conference on Decision and Control

Volumn 5, Issue , 2001, Pages 4760-4765

  Verdult, Vincent ^a   Verhaegen, Michel ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; LINEAR CONTROL SYSTEMS; MATHEMATICAL MODELS; MULTIVARIABLE CONTROL SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; STATE SPACE METHODS; TIME VARYING CONTROL SYSTEMS;

EXTENDED KALMAN SMOOTHER; GRADIENT SEARCH METHOD; LINEAR STATE-SPACE SYSTEM;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 0035707001     PISSN: 01912216     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Nonlinear black-box modeling in system identification: A unified overview
2. Adaptation and learning using multiple models, switching and tuning
3. Estimation of nonlinear systems using linear multiple models
4. Linear dynamic recursive estimation from the viewpoint of regression analysis
5. Local learning algorithms
6. Local learning in local model networks
7. Identifiability issues for parameter-varying and multidimensional linear systems
8. Identification of the deterministic part of MIMO state space models given in innovations form from input-output data