Authors: Alejandro Anderson; Alejandro González; Antonio Ferramosca; Ernesto Kofman.
Resumen: Recently, a Model Predictive Control (MPC) scheme suitable for closed-loop re-identication was proposed which solves, in a non-conservative form, thepotential con ict between the persistent excitation of the system and the stabilization.The idea is to use the concept of probabilistic invariance to dene a target set,and so to take advantage of the knowledge of the probabilistic distribution ofthe excitation signal to design a non-competitive two-objective MPC formulation.Although this proposal seems to work properly from an identication point of view(since uncorrelated output-input data are obtained), some theoretical properties of the formulation remains unexploited. In this work, new results are presented, focusing on the nite-time convergence to the target, which is necessary to start the second MPC objective of identication. Furthermore, several new simulation are developed to clearly show the new properties benets.
Meeting type: Congreso.
Type of job: Artículo Completo.
Production: Extended MPC for closed-loop re-identification based on probabilistic invariant sets.
Scientific meeting: XXVº Congreso Argentino de Control Automático (AADECA 2016).
Meeting place: Buenos Aires.
Organizing Institution: AADECA.
It's published?: Yes
Publication place: Buenos Aires
Meeting month: 11