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710	2		_aSpringerLink (Online service) _9106996
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008			181128s2019 gw a o |||| 0|eng d
020			_a9783030041403
024	7		_a10.1007/978-3-030-04140-3 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aTJ212 _b2019 EB
100	1		_aMhaskar, Prashant _eautor _9671222
245	1	0	_aModeling and Control of Batch Processes : _bTheory and Applications _cby Prashant Mhaskar, Abhinav Garg, Brandon Corbett.
264		1	_aCham _bImprint: Springer _c2019
300			_a1 recurso en línea (XXVI, 335 páginas)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
490	0		_aAdvances in Industrial Control _x1430-9491
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aMotivation -- Part I: First-Principles Model Based Control -- Part II: Integrating Multi-Model Dynamics With PLS Based Approaches -- Part III: Subspace Identification Based Modeling Approach for Batch Processes.
520	3		_aModeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods are specifically tailored to handle issues pertinent to batch processes, such as nonlinear dynamics and lack of online quality measurements. In particular, the book proposes: a novel batch control design with well characterized feasibility properties; a modeling approach that unites multi-model and partial least squares techniques; a generalization of the subspace identification approach for batch processes; and applications to several detailed case studies, ranging from a complex simulation test bed to industrial data. The book's proposed methodology employs statistical tools, such as partial least squares and subspace identification, and couples them with notions from state-space-based models to provide solutions to the quality control problem for batch processes. Practical implementation issues are discussed to help readers understand the application of the methods in greater depth. The book includes numerous comments and remarks providing insight and fundamental understanding into the modeling and control of batch processes. Modeling and Control of Batch Processes includes many detailed examples of industrial relevance that can be tailored by process control engineers or researchers to a specific application. The book is also of interest to graduate students studying control systems, as it contains new research topics and references to significant recent work. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
988			_aPrimersemestre_2019_Robotics
650		7	_2embne _aControl automático _9405125
650		7	_2embne _9143360 _aIngeniería industrial
700	1		_aGarg, Abhinav. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aCorbett, Brandon. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030041397
776	0	8	_iPrinted edition: _z9783030041410
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-04140-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b11/2019 _ek _zSI