LEADER 03426nam  22006135  450 
001 9910438160003321
005 20200630155842.0
010   $a3-319-01288-6
024 7 $a10.1007/978-3-319-01288-9
035   $a(CKB)3710000000024335
035   $a(SSID)ssj0001049498
035   $a(PQKBManifestationID)11678732
035   $a(PQKBTitleCode)TC0001049498
035   $a(PQKBWorkID)11018930
035   $a(PQKB)10424059
035   $a(DE-He213)978-3-319-01288-9
035   $a(MiAaPQ)EBC3107016
035   $a(PPN)176103929
035   $a(EXLCZ)993710000000024335
100   $a20131001d2013      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aInvariance Entropy for Deterministic Control Systems $eAn Introduction /$fby Christoph Kawan
205   $a1st ed. 2013.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2013.
215   $a1 online resource (XXII, 270 p. 2 illus., 1 illus. in color.) 
225 1 $aLecture Notes in Mathematics,$x0075-8434 ;$v2089
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-319-01287-8 
327   $aBasic Properties of Control Systems -- Introduction to Invariance Entropy -- Linear and Bilinear Systems -- General Estimates -- Controllability, Lyapunov Exponents, and Upper Bounds -- Escape Rates and Lower Bounds -- Examples -- Notation -- Bibliography -- Index.
330   $aThis monograph provides an introduction to the concept of invariance entropy, the central motivation of which lies in the need to deal with communication constraints in networked control systems. For the simplest possible network topology, consisting of one controller and one dynamical system connected by a digital channel, invariance entropy provides a measure for the smallest data rate above which it is possible to render a given subset of the state space invariant by means of a symbolic coder-controller pair. This concept is essentially equivalent to the notion of topological feedback entropy introduced by Nair, Evans, Mareels and Moran (Topological feedback entropy and nonlinear stabilization. IEEE Trans. Automat. Control 49 (2004), 1585?1597). The book presents the foundations of a theory which aims at finding expressions for invariance entropy in terms of dynamical quantities such as Lyapunov exponents. While both discrete-time and continuous-time systems are treated, the emphasis lies on systems given by differential equations.
410  0$aLecture Notes in Mathematics,$x0075-8434 ;$v2089
606   $aDynamics
606   $aErgodic theory
606   $aSystem theory
606   $aDynamical Systems and Ergodic Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/M1204X
606   $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070
615  0$aDynamics.
615  0$aErgodic theory.
615  0$aSystem theory.
615 14$aDynamical Systems and Ergodic Theory.
615 24$aSystems Theory, Control.
676   $a515.42
700   $aKawan$b Christoph$4aut$4http://id.loc.gov/vocabulary/relators/aut$0479678
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910438160003321
996   $aInvariance entropy for deterministic control systems$9258671
997   $aUNINA