Iterative minimization of H2 control performance criteria

Data-based control design methods most often consist of iterative adjustment of the controller&psila;s parameters towards the parameter values which minimize an H2 performance criterion. Typically, batches of input-output data collected from the system are used to feed directly a gradient descent optimization - no process model is used. A limiting factor in the application of these methods is the lack of useful conditions guaranteeing convergence to the global minimum; several adaptive control algorithms suffer from the same limitation. In this paper the H2 performance criterion is analyzed in order to characterize and enlarge the set of initial parameter values from which a gradient descent algorithm can converge to its global minimum.


Publié dans:
Automatica, 44, 10, 2549-2559
Année
2008
Mots-clefs:
Laboratoires:




 Notice créée le 2009-01-13, modifiée le 2019-03-16

n/a:
Télécharger le document
PDF

Évaluer ce document:

Rate this document:
1
2
3
 
(Pas encore évalué)