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Model Predictive Control Classical, Robust and Stochastic /
For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical p...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | Advanced Textbooks in Control and Signal Processing,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-24853-0 | ||
| 003 | DE-He213 | ||
| 005 | 20220116061624.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 151201s2016 sz | s |||| 0|eng d | ||
| 020 | |a 9783319248530 |9 978-3-319-24853-0 | ||
| 024 | 7 | |a 10.1007/978-3-319-24853-0 |2 doi | |
| 050 | 4 | |a TJ212-225 | |
| 072 | 7 | |a TJFM |2 bicssc | |
| 072 | 7 | |a GPFC |2 bicssc | |
| 072 | 7 | |a TEC004000 |2 bisacsh | |
| 072 | 7 | |a TJFM |2 thema | |
| 082 | 0 | 4 | |a 629.8312 |2 23 |
| 082 | 0 | 4 | |a 003 |2 23 |
| 100 | 1 | |a Kouvaritakis, Basil. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Model Predictive Control |h [electronic resource] : |b Classical, Robust and Stochastic / |c by Basil Kouvaritakis, Mark Cannon. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2016. | |
| 300 | |a XIII, 384 p. 54 illus., 3 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Advanced Textbooks in Control and Signal Processing, |x 2510-3814 | |
| 505 | 0 | |a From the Contents: Introduction -- Classical Model Predictive Control -- Robust Model Predictive Control with Additive Uncertainty: Open-loop Optimization Strategies -- Robust Model Predictive Control with Additive Uncertainty: Closed-loop Optimization Strategies. | |
| 520 | |a For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses. | ||
| 650 | 0 | |a Control engineering. | |
| 650 | 0 | |a System theory. | |
| 650 | 0 | |a Control theory. | |
| 650 | 0 | |a Chemistry, Technical. | |
| 650 | 0 | |a Automotive engineering. | |
| 650 | 0 | |a Aerospace engineering. | |
| 650 | 0 | |a Astronautics. | |
| 650 | 1 | 4 | |a Control and Systems Theory. |
| 650 | 2 | 4 | |a Systems Theory, Control . |
| 650 | 2 | 4 | |a Industrial Chemistry. |
| 650 | 2 | 4 | |a Automotive Engineering. |
| 650 | 2 | 4 | |a Aerospace Technology and Astronautics. |
| 700 | 1 | |a Cannon, Mark. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319248516 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319248523 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319796895 |
| 830 | 0 | |a Advanced Textbooks in Control and Signal Processing, |x 2510-3814 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-24853-0 |z Texto Completo |
| 912 | |a ZDB-2-ENG | ||
| 912 | |a ZDB-2-SXE | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||