Automotive Model Predictive Control: Models, Methods and Applications(Lecture Notes in Control and Information Sciences, 402)

Luigi del Re

ISBN 10: 1849960704 / ISBN 13: 9781849960700

Published by Springer, 2010

About this Item

This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9781849960700.

Seller Inventory # 8247843

Bibliographic Details

• Title: Automotive Model Predictive Control: Models, Methods and Applications(Lecture Notes in Control and Information Sciences, 402)
• Publisher: Springer
• Publication Date: 2010
• Language: English
• ISBN 10: 1849960704
• ISBN 13: 9781849960700
• Binding: Soft cover
• Condition: Good
• Weight: 650 grams
• Seller catalogs:
  • Engineering

About this title

Synopsis

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.