Conjuntos Invariantes Probabilísticos para la Re-Identificación a Lazo-Cerrado (Probabilistic Invariant Sets for Closed-Loop Re-Identification)

Alejandro Anderson (alelanderson@gmail.com)1, Alejandro Hernán González (alejgon@santafe-conicet.gov.ar)1, Antonio Ferramosca (ferramosca@santafe-conicet.gov.ar)2, Ernesto Kofman (kofman@fceia.unr.edu.ar)3


1Institute of Technological Development for the Chemical Industry (INTEC), CONICET-Universidad Nacional del Litoral (UNL)
2CONICET - Universidad Tecnológica Nacional (UTN). Facultad Regional de Reconquista
3Deparatmento de Control, FCEIA, UNR and CIFASIS-CONICET, Argentina.

This paper appears in: Revista IEEE América Latina

Publication Date: June 2016
Volume: 14,   Issue: 6 
ISSN: 1548-0992


Abstract:
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.

Index Terms:
Model predictive control, closed-loop identification, probabilistic invariant set   


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