It looks like you're offline.
Open Library logo
additional options menu

MARC Record from Library of Congress

Record ID marc_loc_2016/BooksAll.2016.part39.utf8:157555853:2952
Source Library of Congress
Download Link /show-records/marc_loc_2016/BooksAll.2016.part39.utf8:157555853:2952?format=raw

LEADER: 02952cam a2200337 a 4500
001 2011926420
003 DLC
005 20130509082552.0
008 110330s2011 nyua 001 0 eng c
010 $a 2011926420
016 7 $a015767305$2Uk
020 $a9780857295811 (hdbk. : acid-free paper)
020 $a0857295810 (hdbk. : acid-free paper)
035 $a(OCoLC)ocn721889597
040 $aBTCTA$beng$cBTCTA$dYDXCP$dIXA$dCDX$dUKMGB$dDLC
042 $apcc
050 00 $aTJ217.6$b.N48 2011
245 00 $aNetworked and distributed predictive control :$bmethods and nonlinear process network applications /$cPanagiotis D. Christofides, Jinfeng Liu, David Muñoz de la Peña.
260 $aNew York :$bSpringer,$c2011.
300 $a228 p.:$bill. ;$c24 cm.
490 1 $aAdvances in industrial control
504 $aIncludes bibliographical references and index.
520 $aPresents rigorous, yet practical, methods for the design of networked and distributed predictive control systems. The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture development. This shows how networked control can augment dedicated control systems in a natural way and takes advantage of additional, potentially asynchronous and delayed measurements to maintain closed loop stability and significantly to improve closed-loop performance. The text then shifts focus to the design of distributed predictive control systems that cooperate efficiently in computing optimal manipulated input trajectories that achieve desired stability, performance and robustness specifications but spend a fraction of the time required by centralized control systems. Key features of this book include: new techniques for networked and distributed control system design; insight into issues associated with networked and distributed predictive control and their solution; detailed appraisal of industrial relevance using computer simulation of nonlinear chemical process networks and wind and solar energy generation systems; integrated exposition of novel research topics and rich resource of references to significant recent work. The text is intended for academic researchers and graduate students studying control and for process control engineers. The constant attention to practical matters associated with implementation of the theory discussed will help each of these groups understand the application of the book's methods in greater depth--$cSource other than Library of Congress.
650 0 $aPredictive control.
650 0 $aLyapunov functions.
650 0 $aNonlinear control theory.
700 1 $aChristofides, Panagiotis D.
700 1 $aLiu, Jinfeng.
700 1 $aMuñoz de la Peña, David.
830 0 $aAdvances in industrial control.
856 41 $uhttp://dx.doi.org/10.1007/978-0-85729-582-8$yFull text