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Online soft sensor for hybrid systems with mixed continuous and discrete measurements
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SYSNO ASEP 0367111 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Online soft sensor for hybrid systems with mixed continuous and discrete measurements Author(s) Suzdaleva, Evgenia (UTIA-B) RID, ORCID
Nagy, Ivan (UTIA-B) RID, ORCIDNumber of authors 2 Source Title Computers and Chemical Engineering. - : Elsevier - ISSN 0098-1354
Roč. 36, č. 10 (2012), s. 294-300Number of pages 7 s. Language eng - English Country NL - Netherlands Keywords online state prediction ; hybrid filter ; state-space model ; mixed data Subject RIV BC - Control Systems Theory R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) TA01030123 GA TA ČR - Technology Agency of the Czech Republic (TA ČR) CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000298548800025 DOI 10.1016/j.compchemeng.2011.09.004 Annotation Online state prediction and fault detection are typical tasks in the chemical industry. In practice it often happens that some variables, important and critical for quality control, cannot be measured online due to such restrictions as cost and reliability. An uncertainty existing in real systems allows to use a probabilistic approach to online state estimation. Such an approach is proposed in this paper. Different types of information appearing in an online diagnostic system are processed via combination of algorithms subject to probability distributions. This combination of algorithms is presented as a decomposed version of Bayesian filtering. In this paper, the proposed solution is specialized for a system with mixed both continuous and discrete-valued measurements and unobserved variables. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2012
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