Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 175,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 189,08
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 191,23
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 175,26
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Buchpark, Trebbin, Germania
EUR 92,05
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Gut. Zustand: Gut | Seiten: 304 | Sprache: Englisch | Produktart: Bücher | Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility ¿ at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for ¿slow¿ complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for ¿fast¿systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 195,61
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: preigu, Osnabrück, Germania
EUR 150,30
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Automotive Model Predictive Control | Models, Methods and Applications | Luigi Del Re (u. a.) | Taschenbuch | Lecture Notes in Control and Information Sciences | xiv | Englisch | 2010 | Springer | EAN 9781849960700 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 179,61
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility - at the price of complexity and di cult tuning. The progressive evolution has been mainly ledby speci capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for 'slow' complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for 'fast'systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.
Da: Revaluation Books, Exeter, Regno Unito
EUR 247,08
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 1st edition. 284 pages. 9.25x6.25x0.75 inches. In Stock.
EUR 305,92
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2012
ISBN 10: 384733185X ISBN 13: 9783847331858
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 68,00
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In modern automotive industry, the state-of-art technology of fuel injection controllers utilizes feed-forward control with a mass airflow sensor located upstream of the throttle, plus a proportional and integral (PI) type feedback control. The feed-forward control is simply implemented with look-up tables, which requires a laborious process of calibration and tuning. With the development of micro-controllers for engine control units (ECU), a variety of advanced control schemes has been introduced to automotive industry. This research work, firstly, investigated neural network based feed-forward control method to improve the performance of fuel injector. In addition, based on the air/fuel ratio model developed, a nonlinear model predictive control scheme is implemented successfully, and the control performance and robustness are evaluated by introducing system uncertainties.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 134,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Da: moluna, Greven, Germania
EUR 144,94
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives the reader access to the uses of a modern and successful method of control in a most important applications area Presents the points of view of industry-based engineers and academic research to give a balanced, practical b.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 171,19
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility - at the price of complexity and di cult tuning. The progressive evolution has been mainly ledby speci capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for 'slow' complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for 'fast'systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control. 304 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Mär 2010, 2010
ISBN 10: 1849960704 ISBN 13: 9781849960700
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 171,19
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility ¿ at the price of complexity and di cult tuning. The progressive evolution has been mainly ledby speci capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for ¿slow¿ complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for ¿fast¿systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 304 pp. Englisch.