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Analysis of averages over distributions of Markov processes
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-0355-2663
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
2018 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 98, p. 354-357Article in journal (Refereed) Published
Abstract [en]

In problems of optimal control of Markov decision processes and optimal design of experiments, the occupation measure of a Markov process is designed in order to maximize a specific reward function. When the memory of such a process is too long, or the process is non-Markovian but mixing, it makes sense to approximate it by that of a shorter memory Markov process. This note provides a specific bound for the approximation error introduced in these schemes. The derived bound is then applied to the proposed solution of a recently introduced approach to optimal input design for nonlinear systems.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 98, p. 354-357
Keywords [en]
System identification, Input design, Markov chains
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:kth:diva-239469DOI: 10.1016/j.automatica.2018.09.016ISI: 000449310900039Scopus ID: 2-s2.0-85053735276OAI: oai:DiVA.org:kth-239469DiVA, id: diva2:1265717
Note

QC 20181126

Available from: 2018-11-26 Created: 2018-11-26 Last updated: 2019-08-20Bibliographically approved

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Rojas, Cristian R.Hjalmarsson, Håkan

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