INTEC   05402
INSTITUTO DE DESARROLLO TECNOLOGICO PARA LA INDUSTRIA QUIMICA
Unidad Ejecutora - UE
artículos
Título:
Probabilistic Invariant Sets for Closed-Loop Re-Identification
Autor/es:
ALEJANDRO GONZÁLEZ; ALEJANDRO ANDERSON; ERNESTO KOFMAN; ANTONIO FERRAMOSCA
Revista:
IEEE LATIN AMERICA TRANSACTIONS
Editorial:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Referencias:
Lugar: New York; Año: 2016 vol. 14 p. 2744 - 2751
ISSN:
1548-0992
Resumen:
Recently, a Model Predictive Control (MPC) suitable for closed-loop re-identification was proposed, which solves the potential conflict between the persistent excitation of the system and the stabilization of the closed-loop by extending the equilibrium-point-stability to the invariant-set-stability. The proposed objective set, however, derives in large regions that contain conservatively the excited system evolution. In this work, based on the concept of probabilistic invariant sets, the controller target sets are substantially reduced ensuring the invariance with a sufficiently large probability (instead of deterministically), giving the resulting MPC controller the necessary flexibility to be applied in a wide range of systems.