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Axiomatisation of Fully Probabilistic Design Revisited
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SYSNO ASEP 0525231 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Axiomatisation of Fully Probabilistic Design Revisited Author(s) Kárný, Miroslav (UTIA-B) RID, ORCID Article number 104719 Source Title Systems and Control Letters. - : Elsevier - ISSN 0167-6911
Roč. 141, č. 1 (2020)Number of pages 13 s. Publication form Print - P Language eng - English Country NL - Netherlands Keywords Closed-loop control ; Control theory ; Stochastic control ; Stochastic modelling ; Performance indices Subject RIV BC - Control Systems Theory OECD category Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) R&D Projects LTC18075 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Limited access Institutional support UTIA-B - RVO:67985556 UT WOS 000540349700008 EID SCOPUS 85085607647 DOI 10.1016/j.sysconle.2020.104719 Annotation Fully probabilistic design (FPD) of control strategies models both the closed control loop and control objectives by joint probabilities of involved variables. It selects the optimal strategy as the minimiser of Kullback–Leibler (KL) divergence of the closed-loop model to its ideal counterpart expressing the control objectives. Since its proposal (Kárný, 1996) and general algorithmisation (Kárný and Guy, 2006), FPD has been axiomatised (Kárný and Kroupa, 2012) and successfully applied both theoretically (Kárný and Guy, 2012) and practically (Quinn et al., 2003. Kárný et al., 2006)[1]. This paper refines the FPD axiomatisation and bridges FPD to standard stochastic control theory, which it encompasses, in a better way. This enhances applicability of both as well as of its popular, independently proposed, special case known as KL control (Guan et al., 2014). Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2021 Electronic address https://www.sciencedirect.com/science/article/pii/S0167691120301006
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