000 04163nam a22005415i 4500
001 978-3-319-26977-1
003 DE-He213
005 20200421111836.0
007 cr nn 008mamaa
008 151221s2016 gw | s |||| 0|eng d
020 _a9783319269771
_9978-3-319-26977-1
024 7 _a10.1007/978-3-319-26977-1
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aClark, Andrew.
_eauthor.
245 1 0 _aSubmodularity in Dynamics and Control of Networked Systems
_h[electronic resource] /
_cby Andrew Clark, Basel Alomair, Linda Bushnell, Radha Poovendran.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXVII, 210 p. 63 illus., 15 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 _aCommunications and Control Engineering,
_x0178-5354
505 0 _aPart I: Submodular Functions and Optimization -- Submodular Functions and Matroids -- Centralized Submodular Maximization -- Distributed Submodular Maximization -- Submodularity in Dynamics and Control -- Background on Control of Networked Systems -- Submodular Optimization for Smooth Convergence in Networked Systems -- Selecting Catalyst Nodes for Synchronization -- Input Selection for Robustness to Noise -- Input Node Selection under Noise Injection Attacks -- Input Node Selection for Joint Performance and Controllability.
520 _aThis book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllability with provable optimality bounds in static as well as time-varying networks. Throughout the text, the submodular framework is illustrated with the help of numerical examples and application-based case studies in biological, energy and vehicular systems. The book effectively combines two areas of growing interest, and will be especially useful for researchers in control theory, applied mathematics, networking or machine learning with experience in submodular optimization but who are less familiar with the problems and tools available for networked systems (or vice versa). It will also benefit graduate students, offering consistent terminology and notation that greatly reduces the initial effort associated with beginning a course of study in a new area.
650 0 _aEngineering.
650 0 _aSystem theory.
650 0 _aControl engineering.
650 0 _aElectrical engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aSystems Theory, Control.
650 2 4 _aCommunications Engineering, Networks.
700 1 _aAlomair, Basel.
_eauthor.
700 1 _aBushnell, Linda.
_eauthor.
700 1 _aPoovendran, Radha.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319269757
830 0 _aCommunications and Control Engineering,
_x0178-5354
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26977-1
912 _aZDB-2-ENG
942 _cEBK
999 _c55301
_d55301