000 05015nam a22005535i 4500
001 978-3-319-06364-5
003 DE-He213
005 20141015144332.0
007 cr nn 008mamaa
008 140422s2014 gw | s |||| 0|eng d
020 _a9783319063645
_9978-3-319-06364-5
024 7 _a10.1007/978-3-319-06364-5
_2doi
041 _aeng
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aBoutalis, Yiannis.
_eauthor.
245 1 0 _aSystem Identification and Adaptive Control
_h[electronic resource] :
_bTheory and Applications of the Neurofuzzy and Fuzzy Cognitive Network Models /
_cby Yiannis Boutalis, Dimitrios Theodoridis, Theodore Kottas, Manolis A. Christodoulou.
260 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXII, 313 p. 120 illus., 56 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 _aAdvances in Industrial Control,
_x1430-9491
505 0 _aPart I The Recurrent Neurofuzzy Model -- Introduction and Scope -- Identification of Dynamical Systems Using Recurrent Neurofuzzy Modeling -- Indirect Adaptive Control Based on the Recurrent Neurofuzzy Model -- Direct Adaptive Neurofuzzy Control of SISO Systems -- Direct Adaptive Neurofuzzy Control of MIMO Systems -- Selected Applications -- Part II The Fuzzy Cognitive Network Model: Introduction and Outline -- Existence and Uniqueness of Solutions in FCN -- Adaptive Estimation Algorithms of FCN Parameters -- Framework of Operation and Selected Applications.
520 _aPresenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented.  Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model  stems  from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems.  All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: •             contemporary power generation; •             process control; and •             conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control. aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aIndustrial engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputational Intelligence.
650 2 4 _aIndustrial and Production Engineering.
700 1 _aTheodoridis, Dimitrios.
_eauthor.
700 1 _aKottas, Theodore.
_eauthor.
700 1 _aChristodoulou, Manolis A.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319063638
830 0 _aAdvances in Industrial Control,
_x1430-9491
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-06364-5
912 _aZDB-2-ENG
942 _cEB
999 _c14232
_d14232