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001 978-3-031-22140-8
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008 230313s2023 sz | s |||| 0|eng d
020 _a9783031221408
_9978-3-031-22140-8
024 7 _a10.1007/978-3-031-22140-8
_2doi
050 4 _aTK7895.E42
050 4 _aTK5105.8857
072 7 _aTJF
_2bicssc
072 7 _aGPFC
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072 7 _aTEC008000
_2bisacsh
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_2thema
072 7 _aGPFC
_2thema
082 0 4 _a621.38
_223
100 1 _aViola, Jairo.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984581
245 1 0 _aDigital-Twin-Enabled Smart Control Engineering
_h[electronic resource] :
_bA Framework and Case Studies /
_cby Jairo Viola, YangQuan Chen.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2023.
300 _aXII, 111 p. 67 illus., 61 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 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
505 0 _aDigital Twin Background -- A Digital Twin Development Framework -- Digital Twin Enabling Capabilities -- Smart Control Engineering Enabled by Digital Twin -- Summary and Future Research Opportunities.
520 _aThis book presents a novel design framework for the development of Digital Twin (DT) models for process- and motion-control applications. It is based on system-data acquisition using cutting-edge computing technologies, modelling of physical-system behavior through detailed simultaneous simulation of different aspects of the system, and optimal dynamic behavior-matching of the process. The design framework is enhanced with real-time data analytics to improve the performance of the DT's behavior-matching with the real system or physical twin. The methods of creating a DT detailed in Digital-Twin-Enabled Smart Control Engineering make possible the study of a system for real-time controller tuning and fault detection. They also facilitate life-cycle analysis for multiple critical and dangerous conditions that cannot be explored in the corresponding real system or physical twin. The authors show how a DT can be exploited to enable self-optimizing capabilities in feedback control systems. The DT framework and the control-performance assessment, fault diagnosis and prognosis, remaining-useful-life analysis, and self-optimizing control abilities it allows are validated with both process- and motion-control systems and their DTs. Supporting MATLAB-based material for a case study and an expanded introduction to the basic elements of DTs can be accessed on an associated website. This book helps university researchers from many areas of engineering to develop new tools for control design and reliability and life-cycle assessment and helps practicing engineers working with robotic, manufacturing and processing, and mechatronic systems to maintain and develop the mechanical tools they use.
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aIndustrial engineering.
_931641
650 0 _aAutomation.
_92392
650 0 _aControl engineering.
_931970
650 0 _aComputer simulation.
_95106
650 0 _aDynamics.
_984583
650 0 _aNonlinear theories.
_93339
650 1 4 _aCyber-Physical Systems.
_932475
650 2 4 _aIndustrial Automation.
_946517
650 2 4 _aControl and Systems Theory.
_931972
650 2 4 _aComputer Modelling.
_984586
650 2 4 _aApplied Dynamical Systems.
_932005
700 1 _aChen, YangQuan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984588
710 2 _aSpringerLink (Online service)
_984590
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031221392
776 0 8 _iPrinted edition:
_z9783031221415
776 0 8 _iPrinted edition:
_z9783031221422
830 0 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
_984591
856 4 0 _uhttps://doi.org/10.1007/978-3-031-22140-8
912 _aZDB-2-SXSC
942 _cEBK
999 _c85687
_d85687