Convergence in nonlinear optimal sampled-data control problems
Résumé
Consider, on the one part, a general nonlinear finite-dimensional optimal control problem and assume that it has a unique solution whose state is denoted by x*. On the other part, consider the sampled-data control version of it. Under appropriate assumptions, we prove that the optimal state of the sampled-data problem converges uniformly to x* as the norm of the corresponding partition tends to zero. Moreover, applying the Pontryagin maximum principle to both problems, we prove that, if x* has a unique weak extremal lift with a costate p that is normal, then the costate of the sampled-data problem converges uniformly to p. In other words, under a nondegeneracy assumption, control sampling commutes, at the limit of small partitions, with the application of the Pontryagin maximum principle.
Fichier principal
sampling.pdf (274.33 Ko)
Télécharger le fichier
bibIEEEbourdintrelat.bib (17.65 Ko)
Télécharger le fichier
Origine | Fichiers produits par l'(les) auteur(s) |
---|