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001			286047
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007			cr nn 008mamaa
008			150903s2010 xxu| o |||| 0|eng d
020			_a9781441906304 _99781441906304
024	7		_a10.1007/9781441906304 _2doi
035			_avtls000338056
039		9	_a201509030810 _bVLOAD _c201404300339 _dVLOAD _y201402060901 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ295
100	1		_aDragan, Vasile. _eautor _9300693
245	1	0	_aMathematical Methods in Robust Control of Discrete-Time Linear Stochastic Systems / _cby Vasile Dragan, Toader Morozan, Adrian-Mihail Stoica.
250			_aFirst.
264		1	_aNew York, NY : _bSpringer New York, _c2010.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aElements of probability theory -- Discrete-time linear equations defined by positive operators -- Mean square exponential stability -- Structural properties of linear stochastic systems -- Discrete-time Riccati equations of stochastic control -- Linear quadratic optimization problems -- Discrete-time stochastic optimal control -- Robust stability and robust stabilization of discrete-time linear stochastic systems.
520			_aIn this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors’ work presented in their previous book entitled "Mathematical Methods in Robust Control of Linear Stochastic Systems" published by Springer in 2006. Key features: - Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature - Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains - Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations - Leads the reader in a natural way to the original results through a systematic presentation - Presents new theoretical results with detailed numerical examples The monograph is geared to researchers and graduate students in advanced control engineering, applied mathematics, mathematical systems theory and finance. It is also accessible to undergraduate students with a fundamental knowledge in the theory of stochastic systems.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aMorozan, Toader. _eautor _9300694
700	1		_aStoica, Adrian-Mihail. _eautor _9300695
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781441906298
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4419-0630-4 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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