Consistent and computationally efficient estimation for stochastic LPV state-space models: realization based approach
Résumé
The article presents an identification algorithm for stochastic Linear Parameter-Varying State-Space Affine (LPVSSA) representations, where the dependency of state-space matrices on scheduling signals is affine. Based on stochastic realization theory, a computationally efficient and statistically consistent identification algorithm is proposed to estimate the LPV model matrices, which are computed from the empirical covariance matrices of outputs and scheduling signal observations. The effectiveness of the proposed realization algorithm is shown via a numerical case study.
Fichier principal
Realization_Stoch_LPV_V12_Final_cdc_reduced.pdf (284.32 Ko)
Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)