To access the full text documents, please follow this link: http://hdl.handle.net/2117/83901

Title:	Non-linear set-membership identification approach based on the Bayesian framework
Author:	Fernández Canti, Rosa M.; Tornil Sin, Sebastián; Blesa Izquierdo, Joaquim; Puig Cayuela, Vicenç
Other authors:	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy; Universitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control; Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
Abstract:	This study deals with the problem of set-membership identification of non-linear-in-the-parameters models. To solve this problem, this study illustrates how the Bayesian approach can be used to determine the feasible parameter set (FPS) by assuming uniform distributed estimation error and flat model prior probability distributions. The key point of the methodology is the interval evaluation of the likelihood function and the result is a set of boxes with associated credibility indices. For each box, the credibility index is in the interval (0, 1] and gives information about the amount of consistent models inside the box. The union of the boxes with credibility value equal to one provides an inner approximation of the FPS, whereas the union of all boxes provides an outer estimation. The boxes with credibility value smaller than one are located around the boundary of the FPS and their credibility index can be used to iteratively refine the inner and outer approximations up to a desired precision. The main issues and performance of the developed algorithms are discussed and illustrated by means of examples.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Informàtica::Automàtica i control -Control theory -Interval-analysis -State estimation -Bounded-error -Time-systems -Approximation -Observer -Nonlinear programming -Optimisation -Set-membership identification -Bayesian approaches -Parameter estimation -Control, Teoria de
Rights:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Article
Share:

Show full item record