000			03441nam a22004335i 4500
001			u370573
003			SIRSI
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007			cr nn 008mamaa
008			110408s2011 xxk| s |||| 0|eng d
020			_a9780857295019 _9978-0-85729-501-9
040			_cMX-MeUAM
050		4	_aTJ212-225
082	0	4	_a629.8 _223
100	1		_aGrüne, Lars.
245	1	0	_aNonlinear Model Predictive Control _h[recurso electrónico] : _bTheory and Algorithms / _cby Lars Grüne, Jürgen Pannek.
260			_aLondon : _bSpringer London, _c2011.
300			_aXII, 370p. 64 illus., 9 illus. in color. _bdigital.
490	0		_aCommunications and Control Engineering, _x0178-5354
505	0		_a<P>Introduction -- Discrete-time and Sampled-data Systems -- Nonlinear Model Predictive Control -- Infinite-horizon Optimal Control -- Stability and Suboptimality Using Stabilizing Constraints -- Stability and Suboptimality without Stabilizing Constraints -- Feasibility and Robustness -- Numerical Discretization -- Numerical Optimal Control of Nonlinear Systems -- Examples -- Appendix: Brief Introduction to NMPC Software.</P>.
520			_a<p>Nonlinear model predictive control (NMPC) is widely used in the process and chemical industries and increasingly for applications, such as those in the automotive industry, which use higher data sampling rates.</p><p><i>Nonlinear Model Predictive Control</i> is a thorough and rigorous introduction to NMPC for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB and C++(downloadable from http://www.nmpc-book.com/ ) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.</p><p><i>Nonlinear Model Predictive Control</i> is primarily aimed at academic researchers and practitioners working in control and optimisation but the text is self-contained featuring background material on infinite-horizon optimal control and Lyapunov stability theory which makes the book accessible to graduate students of control engineering and applied mathematics..</p>
650		0	_aEngineering.
650		0	_aChemical engineering.
650		0	_aSystems theory.
650	1	4	_aEngineering.
650	2	4	_aControl.
650	2	4	_aSystems Theory, Control.
650	2	4	_aIndustrial Chemistry/Chemical Engineering.
650	2	4	_aAutomotive Engineering.
700	1		_aPannek, Jürgen.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780857295002
830		0	_aCommunications and Control Engineering, _x0178-5354
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-0-85729-501-9
596			_a19
942			_cLIBRO_ELEC
999			_c198453 _d198453