000			04497nam a22004095i 4500
999			_c120692 _d120692
001			120692
003			ES-MaUEC
005			20230102114055.0
006			a||||fo|||| 00| 0
007			cr nn nnnaamaa
008			200519s2020 xxka o |||| 0|eng d
020			_a9781447174578
024	7		_a10.1007/978-1-4471-7457-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA402.35 _b2020 EB
100	1		_aGrimble, Michael J. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/n85286507 _1http://viaf.org/viaf/165400500 _9675012
245	1	0	_aNonlinear Industrial Control Systems : _bOptimal Polynomial Systems and State-Space Approach _cby Michael J. Grimble, Paweł Majecki
250			_aFirst edition
264		1	_aLondon _bSpringer London : _bImprint: Springer _c2020
300			_a1 recurso en línea (XXX, 764 páginas) _b305 ilustraciones, 274 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aPart I: Background -- Introduction to Nonlinear Systems -- Nonlinear Systems Modelling and Identification -- Part II: Polynomial Systems -- Introduction to Nonlinear Generalized Minimum Variance Control -- Nonlinear Generalized Minimum Variance Control Design Issues -- Introduction to Factorised NGMV Nonlinear Controls -- H-infinity Robust Control for Nonlinear Systems -- Design Procedures in the Presence of Saturation and Other Nonlinearities -- Part III: State-space Systems -- Space Approach to NGMV Control -- Design Issues and NGMV Predictive Control -- Basic and Factorised NGMV Control of Continuous-time Systems -- Part IV: Nonlinear System Benchmarking Nonlinear Controls -- Dual Nonlinear Estimation Problems -- Neural Networks, Fuzzy Control and Learning -- Part V: Industrial Applications -- Nonlinear Industrial Process Control Applications -- Nonlinear Automotive, Aerospace and Marine Applications.
520	3		_aNonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB® toolbox (downloadable from www.springer.com/978-1-4471-7455-4) that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems. The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers: different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid; design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H∞ design methods; design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing; steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID. Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.
988			_aSpringer_Robotics_23062020
650		7	_2embne _aSistemas de control no lineal _9666986
700	1		_aMajecki, Paweł _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9675013
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729
776	0	8	_iPrinted edition: _z9781447174554
776	0	8	_iPrinted edition: _z9781447174561
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-4471-7457-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2020 _dz _eIG _zSI