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001 978-981-97-8281-9
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008 250103s2024 si | s |||| 0|eng d
020 _a9789819782819
_9978-981-97-8281-9
024 7 _a10.1007/978-981-97-8281-9
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aGPFC
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aTJFM
_2thema
100 1 _aShen, Dong.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_990107
245 1 0 _aVariable Gain Design in Stochastic Iterative Learning Control
_h[electronic resource] /
_cby Dong Shen.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXI, 350 p. 101 illus., 100 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 _aIntelligent Control and Learning Systems,
_x2662-5466 ;
_v13
505 0 _aIntroduction -- Preliminary Results -- Decreasing Gain Design -- Adaptive Gain Design -- Event triggering Gain Design -- Optimal Gain Design -- Conclusions and Open Problems -- References.
520 _aThis book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.
650 0 _aControl engineering.
650 0 _aStochastic processes.
_976770
650 0 _aSystem theory.
_966519
650 0 _aControl theory.
_968675
650 0 _aIndustrial engineering.
650 0 _aAutomation.
_959149
650 1 4 _aControl and Systems Theory.
_965868
650 2 4 _aStochastic Systems and Control.
_987229
650 2 4 _aSystems Theory, Control.
_968676
650 2 4 _aIndustrial Automation.
_966585
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819782802
776 0 8 _iPrinted edition:
_z9789819782826
776 0 8 _iPrinted edition:
_z9789819782833
830 0 _aIntelligent Control and Learning Systems,
_x2662-5466 ;
_v13
_974070
856 4 0 _uhttps://doi.org/10.1007/978-981-97-8281-9
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c66319
_d66319