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

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 initi...

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Bibliographic Details
Published inInformation sciences Vol. 369; pp. 287 - 303
Main Authors de Jesus, Gildson Q., Inoue, Roberto S., Terra, Marco H.
Format Journal Article
LanguageEnglish
Published Elsevier Inc 10.11.2016
Subjects
Algorithms
Array algorithm
Arrays
Discrete-time
Information filter
Initial conditions
Linear systems
Markov processes
Markovian jump
Mathematical models
Mobile robot
Robots
Robust estimation
Uncertainty
Array algorithm
Robust estimation
Discrete-time
Mobile robot
Markovian jump
Information filter
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ISSN0020-0255
1872-6291
DOI10.1016/j.ins.2016.06.022

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Summary: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.
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ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2016.06.022