TY - JOUR
T1 - Theoretical and algorithmic advances in multi-parametric programming and control
AU - Pistikopoulos, Efstratios N.
AU - Dominguez, Luis
AU - Panos, Christos
AU - Kouramas, Konstantinos
AU - Chinchuluun, Altannar
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The financial support of European Research Council (MOBILE ERC AdvancedGrant,no:226462),EPSRC(ProjectsGR/T02560/01,EP/E047017,EP/E054285/1)andEuropeanCommis-sion (PROMATCH Marie Curie MRTN-CT-2004-512441, PRISM Marie Curie MTKI-CT-2004-512233,DIAMANTE ToK Project MTKI-CT-2005-IAP-029544, HY2SEP RTD Project 019887, CONNECTCOOP-CT-2006-031638), Air Products, CPSE Industrial Consortium and KAUST is kindly acknowledged.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2012/4/21
Y1 - 2012/4/21
N2 - This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
AB - This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
UR - http://hdl.handle.net/10754/599980
UR - http://link.springer.com/10.1007/s10287-012-0144-4
UR - http://www.scopus.com/inward/record.url?scp=84860637133&partnerID=8YFLogxK
U2 - 10.1007/s10287-012-0144-4
DO - 10.1007/s10287-012-0144-4
M3 - Article
SN - 1619-697X
VL - 9
SP - 183
EP - 203
JO - Computational Management Science
JF - Computational Management Science
IS - 2
ER -