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020 _a9783658359294
024 7 _a10.1007/978-3-658-35929-4
_2doi
040 _aTR-AnTOB
_beng
_erda
_cTR-AnTOB
041 _aeng
060 _aQU 26.5
072 7 _aMQW
_2bicssc
072 7 _aTEC059000
_2bisacsh
072 7 _aMQW
_2thema
096 _aQU26.5EBK
100 1 _aZhang, Zhihua.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aObserver Design for Control and Fault Diagnosis of Boolean Networks
_h[electronic resource] /
_cby Zhihua Zhang.
250 _a1st ed. 2022.
264 1 _aWiesbaden :
_bSpringer Fachmedien Wiesbaden :
_bImprint: Springer Vieweg,
_c2022.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- Matrix expression of Boolean control networks -- Reconstructibility analysis -- Observer design -- Model-based output tracking control -- Model-based Fault diagnosis -- Conclusion -- Kurzfassung in deutscher Sprache (extended summary in German).
520 _aBoolean control networks (BCNs) are a kind of parameter-free model, which can be used to approximate the qualitative behavior of biological systems. After converting into a model similar to the standard discrete-time state-space model, control-theoretic problems of BCNs can be studied. In control theory, state observers can provide state estimation for any other applications. Reconstructibility condition is necessary for the existence of state observers. In this thesis explicit and recursive methods have been developed for reconstructibility analysis. Then, an approach to design Luenberger-like observer has been proposed, which works in a two-step process (i.e. predict and update). If a BCN is reconstructible, then an accurate state estimate can be provided by the observer no later than the minimal reconstructibility index. For a wide range of applications the approach has been extended to enable design of unknown input observer, distributed observers and reduced-order observer. The performance of the observers has been evaluated thoroughly. Furthermore, methods for output tracking control and fault diagnosis of BCNs have been developed. Finally, the developed schemes are tested with numerical examples. About the author Zhihua Zhang received the B.Sc. degree and M.Sc. degree in electrical engineering from the TU Kaiserslautern, Germany, respectively, in 2013 and 2015. In 2021 he finished Ph.D. in the area of Boolean control networks.
650 0 _aBiomedical engineering.
650 0 _aBionics.
650 0 _aComputer science.
650 1 4 _aBiomedical Engineering and Bioengineering.
650 2 4 _aBioinspired Technologies.
650 2 4 _aTheory of Computation.
650 2 4 _aModels of Computation.
653 0 _aSystems Biology
653 0 _aControl theory
710 2 _aSpringerLink (Online service)
856 4 0 _uhttps://doi.org/10.1007/978-3-658-35929-4
_3Springer eBooks
_zOnline access link to the resource
942 _2NLM
_cEBK