000 03547nam a22005055i 4500
001 978-94-007-0741-2
003 DE-He213
005 20140220083831.0
007 cr nn 008mamaa
008 110223s2011 ne | s |||| 0|eng d
020 _a9789400707412
_9978-94-007-0741-2
024 7 _a10.1007/978-94-007-0741-2
_2doi
050 4 _aTA342-343
072 7 _aPBWH
_2bicssc
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aTEC009060
_2bisacsh
082 0 4 _a003.3
_223
100 1 _aLi, Han-Xiong.
_eauthor.
245 1 0 _aSpatio-Temporal Modeling of Nonlinear Distributed Parameter Systems
_h[electronic resource] :
_bA Time/Space Separation Based Approach /
_cby Han-Xiong Li, Chenkun Qi.
264 1 _aDordrecht :
_bSpringer Netherlands,
_c2011.
300 _aXVIII, 178p. 107 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems, Control and Automation: Science and Engineering ;
_v50
520 _aThe purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.                  
650 0 _aMathematics.
650 0 _aChemical engineering.
650 0 _aComputer simulation.
650 1 4 _aMathematics.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aControl.
650 2 4 _aIndustrial Chemistry/Chemical Engineering.
650 2 4 _aSimulation and Modeling.
700 1 _aQi, Chenkun.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789400707405
830 0 _aIntelligent Systems, Control and Automation: Science and Engineering ;
_v50
856 4 0 _uhttp://dx.doi.org/10.1007/978-94-007-0741-2
912 _aZDB-2-ENG
999 _c109368
_d109368