000			05773nam a22003975i 4500
999			_c103914 _d103914 _x1
001			103914
003			DE-He213
005			20230102113151.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			151223s2015 gw | s |||| 0|eng d
020			_a9783319266879
024	7		_a10.1007/978-3-319-26687-9 _2doi
040			_bspa _dES-MaUEC
050		4	_aTJ213 _b2015 EB
245	1	0	_aDevelopments in Model-Based Optimization and Control _bDistributed Control and Industrial Applications _cedited by Sorin Olaru, Alexandra Grancharova, Fernando Lobo Pereira.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XVIII, 381 páginas 115 ilustraciones, 31 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aLecture Notes in Control and Information Sciences, _x0170-8643 ; _v464
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction -- 1. Complexity Certifications of First Order Inexact Lagrangian Methods for General Convex Programming: Application to Real-time MPC -- 2. Fully Inverse Parametric Linear/Quadratic Programming Problems via Convex Liftings -- 3. Implications of Inverse Parametric Optimization in Model Predictive Control -- 4. Distributed Robust Model Predictive Control of Interconnected Polytopic Systems -- 5. Optimal Distributed-Coordinated Approach for Energy Management in Multisource Electric Power Generation Systems -- 6. Evolutionary-game-based Dynamical Tuning for Multi-objective Model Predictive Control -- 7. A Model Predictive Control-based Architecture for Cooperative Path-following of Multiple Unmanned Aerial Vehicles -- 8. Predictive Control for Path Following. From Trajectory Generation to the Parameterization of the Discrete Tracking Sequences -- 9. Formation Reconfiguration using Model Predictive Control Techniques for Multi-Agent Dynamical Systems -- 10. Optimal Operation of a Lumostatic Microalgae Cultivation Process -- 11. Bioprocesses Parameter Estimation by Heuristic Optimization Techniques -- 12. Real-time Experimental Implementation of Predictive Control Schemes in a Small-scale Pasteurization Plant -- 13. An Optimization-based Framework for Impulsive Control Systems -- 14. Robustness Issues in Control of Bilinear Discrete-Time Systems - Applied to the Control of Power Converters -- 15. On the LPV Control Design and its Applications to Some Classes of Dynamical Systems -- 16. Ultimate Bounds and Robust Invariant Sets for Linear Systems with State-dependent Disturbances -- 17. RPI Approximations of the mRPI Set Characterizing Linear Dynamics with Zonotopic Disturbances. .
520	3		_aThis book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and design; and · applications to bioprocesses, multivehicle systems or energy management. The various contributions cover a subject spectrum including inverse optimality and more modern decentralized and cooperative formulations of receding-horizon optimal control. Readers will find fourteen chapters dedicated to optimization-based tools for robustness analysis, and decision-making in relation to feedback mechanisms-fault detection, for example-and three chapters putting forward applications where the model-based optimization brings a novel perspective. Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-based Control and Estimation workshops held in November 2013 and November 2014. It forms a useful resource for academic researchers and graduate students interested in the state of the art in predictive control. Control engineers working in model-based optimization and control, particularly in its bioprocess applications will also find this collection instructive.
988			_aEBSPRINGER_2018
650		7	_2embne _aControl automático _9405125
700	1		_aOlaru, Sorin. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/nb2013011701 _1http://viaf.org/viaf/217289458/ _998103
700	1		_aGrancharova, Alexandra. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/nb2012011417 _1http://viaf.org/viaf/244825672/
700	1		_aLobo Pereira, Fernando. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _1http://viaf.org/viaf/33257042/
776	0	8	_iEdición impresa: _z9783319266855
776	0	8	_iEdición impresa: _z9783319266862
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-26687-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2019 _dz _ejf _zSI