Gradient Projection based Algorithm for Large Scale Real Time Model Predictive Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00180806" target="_blank" >RIV/68407700:21230/11:00180806 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Gradient Projection based Algorithm for Large Scale Real Time Model Predictive Control
Original language description
In model predictive control (MPC), the quadratic program (QP) is solved at each sampling time, thus a fast and effective on-line solver must be used for short sampling times. The multi-parametric quadratic programming (mp-QP) (explicit solution) is impossible to use for larger systems due to the memory limitation. The objective of this paper is to present an effective on-line solver for large-scale simple constrained quadratic programming which arises in the MPC framework. The presented algorithm uses the combination of gradient and Newton projection method to obtain super-linear convergent algorithm which is very close to optimum in very few iterations when many constraints are active in optimum and it does not involve the exact computation of the Newton step at each iteration.
Czech name
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Czech description
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2011 Chinese Control and Decision Conference
ISBN
978-1-4244-8736-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
3906-3911
Publisher name
Northeastern University
Place of publication
Shenyang
Event location
Mianyang
Event date
May 23, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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