Information filtering and array algorithms for discrete-time Markovian jump linear systems subject to parametric uncertainties

Autor(es)

de Jesus, Gildson Q. ; Inoue, Roberto S. ; Terra, Marco H.

• Tipo de documento: Artigo Científico
• Fonte: INFORMATION SCIENCES; v. 369, p. 287-303, NOV 10 2016.
• Citações Web of Science: 3

Resumo

In this paper we present robust information filters for discrete-time Markovian jump linear systems subject to uncertainties in the parameters. We provide recursive estimations to deal with jumps, uncertainties, and unknown initial conditions of the Markovian states. The difficulty in defining initial conditions for this class of systems where the Markov chain is also unknown, justifies the use of information type filters. As an alternative computation method we develop array and fast array algorithms to estimate these uncertain informations. We present numerical examples to demonstrate the efectiveness of the array algorithms proposed. We present also simulation results related with the application of the robust information filter to solve mobile robot localization problems. (C) 2016 Elsevier Inc. All rights reserved. (AU)

• Processo FAPESP: 14/08432-0 - Sistema de referência de atitude, orientação e posição baseado em Filtro de Kalman robusto implementado em FPGA
• Beneficiário: Marco Henrique Terra
• Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Regular