Please use this identifier to cite or link to this item:
Type: Artigo
Title: Filtering of poorly known systems: estimation variations as source of uncertainty
Author: Fernandes, Marcos R.
Val, João B. R. do
Souto, Rafael F.
Abstract: This paper presents a mathematical framework for state estimation of dynamic systems for which only a simplified and rough model is available, using an approach that considers estimation variation itself as a possible source of uncertainty. The discrete-time case is studied and the filtering problem is solved, using a modified version of the Regularized Least Squares (RLS) and tools from the nonsmooth analysis. The solution points to a region in the innovation space in which no variation of estimation is optimal. An algorithm for real-time applications is presented and a numeric example is included to illustrate the benefits of this approach
Subject: Matemática
Country: Estados Unidos
Editor: Institute of Electrical and Electronics Engineers
Rights: Fechado
Identifier DOI: 10.1109/CDC.2018.8619306
Date Issue: 2019
Appears in Collections:FEEC - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-85062171656.pdf507.64 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.