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020 _a9783031581564
_9978-3-031-58156-4
024 7 _a10.1007/978-3-031-58156-4
_2doi
050 4 _aQ295
050 4 _aQA402.3-402.37
072 7 _aGPFC
_2bicssc
072 7 _aSCI064000
_2bisacsh
072 7 _aGPFC
_2thema
100 1 _aOuvrard, Régis.
_eauthor.
_0(orcid)0000-0003-0534-4497
_1https://orcid.org/0000-0003-0534-4497
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983592
245 1 0 _aPartial Moments in System Identification
_h[electronic resource] /
_cby Régis Ouvrard, Thierry Poinot, Jean-Claude Trigeassou.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 172 p. 37 illus., 34 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Control and Information Sciences,
_x1610-7411 ;
_v494
505 0 _aChapter 1. An introduction about moments in identification -- Chapter 2. An introductory example -- Chapter 3. Partial moments in continuous-time -- Chapter 4. Partial moments in discrete-time -- Chapter 5. Algebraic identification, a partial moment approach -- Chapter 6. Continuous-time subspace based method -- Chapter 7. Continuous-time linear parameter varying model -- Chapter 8. Multidimensional partial moments -- Chapter 9. Perspectives -- Referrences.
520 _aThis book provides a complete round-up of developments concerned with the application of partial moments in system identification and data-driven modelling; it captures the essence of work carried out at the Laboratoire d'Informatique et d'Automatique pour les Systèmes for more than 40 years. The book begins with introductory material, describing both the mathematical tools associated with partial moments and reinitialized partial moments and an example demonstrating their use. The authors then proceed to show how these tools can be used for the identification of continuous-time linear models, discrete-time linear models, continuous-time linear state-space models, linear parameter-varying models and multidimensional models based on partial differential equations. The properties and performances of each of these approaches are presented. The analogy with algebraic approaches is proved, thus opening perspectives for extension to other fields. The text removes some long-standing limitations on the implementation of partial-moment-based tools in system identification. This book is of interest to researchers and postgraduates studying system identification, control theory, applied mathematics and computer science. It is also useful for engineers working on industrial applications of parametric estimation of mathematical models. .
650 0 _aSystem theory.
_966519
650 0 _aControl theory.
_968675
650 0 _aControl engineering.
650 0 _aDifferential equations.
650 0 _aComputer science
_xMathematics.
_964041
650 0 _aDiscrete mathematics.
650 1 4 _aSystems Theory, Control.
_968676
650 2 4 _aControl and Systems Theory.
_965868
650 2 4 _aDifferential Equations.
650 2 4 _aDiscrete Mathematics in Computer Science.
700 1 _aPoinot, Thierry.
_eauthor.
_0(orcid)0000-0003-1533-126X
_1https://orcid.org/0000-0003-1533-126X
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983593
700 1 _aTrigeassou, Jean-Claude.
_eauthor.
_0(orcid)0000-0003-2587-9958
_1https://orcid.org/0000-0003-2587-9958
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983594
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031581557
776 0 8 _iPrinted edition:
_z9783031581571
776 0 8 _iPrinted edition:
_z9783031581588
830 0 _aLecture Notes in Control and Information Sciences,
_x1610-7411 ;
_v494
_973486
856 4 0 _uhttps://doi.org/10.1007/978-3-031-58156-4
912 _aZDB-2-ENG
912 _aZDB-2-SXE
912 _aZDB-2-LNI
999 _c63050
_d63050