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007			cr nn 008mamaa
008			110407s2011 xxk| s |||| 0|eng d
020			_a9780857295828 _9978-0-85729-582-8
040			_cMX-MeUAM
050		4	_aTJ212-225
082	0	4	_a629.8 _223
100	1		_aChristofides, Panagiotis D. _eauthor.
245	1	0	_aNetworked and Distributed Predictive Control _h[recurso electrónico] : _bMethods and Nonlinear Process Network Applications / _cby Panagiotis D. Christofides, Jinfeng Liu, David Muñoz de la Peña.
264		1	_aLondon : _bSpringer London, _c2011.
300			_aXXVIII, 232 p. _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		_aIntroduction -- Lyapunov-based Model Predictive Control -- Networked Predictive Process Control -- Distributed Model Predictive Control -- Sequential and Iterative Distributed Model Predictive Control -- Multirate Distributed Model Predictive Control.
520			_aNetworked and Distributed Predictive Control presents 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 to account 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 utilize 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 problems; ·         detailed appraisal of industrial relevance using computer simulation of nonlinear chemical process networks and wind- and solar-energy-generation systems; and ·         integrated exposition of novel research topics and rich resource of references to significant recent work. A full understanding of Networked and Distributed Predictive Control requires a basic knowledge of differential equations, linear and nonlinear control theory and optimization methods and the book is intended for academic researchers and graduate students studying control as well as for process control engineers. The constant attention to practical matters associated with implementation of the theory discussed will help researchers and engineers understand the application of the book’s methods in greater depth.
650		0	_aEngineering.
650		0	_aChemical engineering.
650		0	_aComputer Communication Networks.
650		0	_aSystems theory.
650		0	_aRenewable energy sources.
650	1	4	_aEngineering.
650	2	4	_aControl.
650	2	4	_aIndustrial Chemistry/Chemical Engineering.
650	2	4	_aRenewable and Green Energy.
650	2	4	_aSystems Theory, Control.
650	2	4	_aComputer Communication Networks.
700	1		_aLiu, Jinfeng. _eauthor.
700	1		_aMuñoz de la Peña, David. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780857295811
830		0	_aAdvances in Industrial Control, _x1430-9491
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-0-85729-582-8
596			_a19
942			_cLIBRO_ELEC
999			_c198469 _d198469