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Input design using Markov chains for system identification
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control. (System Identification Group)ORCID iD: 0000-0002-1927-1690
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control. (System Identification Group)ORCID iD: 0000-0003-0355-2663
2009 (English)In: Proceedings of the 48th IEEE Conference on  Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009, IEEE conference proceedings, 2009, 1557-1562 p.Conference paper (Refereed)
Abstract [en]

This paper studies the input design problem for system identification where time domain constraints have to be considered. A finite Markov chain is used to model the input of the system. This allows to directly include input amplitude constraints in the input model by properly choosing the state space of the Markov chain, which is defined so that the Markov chain generates a multi-level sequence. The probability distribution of the Markov chain is shaped in order to minimize the cost function considered in the input design problem. Stochastic approximation is used to minimize that cost function. With this approach, the input signal to apply to the system can be easily generated by extracting samples from the optimal distribution. A numerical example shows how this method can improve estimation with respect to other input realization techniques.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2009. 1557-1562 p.
Keyword [en]
Finite Markov chain, Input design, Input models, Input signal, Markov Chain, Multi-level, Numerical example, Optimal distributions, State space, Stochastic approximations, System identifications, Time domain constraints, Approximation theory, Cost functions, Design, Extraction, Markov processes, Mobile telecommunication systems, Probability distributions, Identification (control systems)
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-28498DOI: 10.1109/CDC.2009.5400423ScopusID: 2-s2.0-77950795043OAI: diva2:390941
48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009; Shanghai
Swedish Research Council
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20110124Available from: 2012-01-02 Created: 2011-01-14 Last updated: 2013-09-05Bibliographically approved

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