Theoretical and algorithmic advances in multi-parametric programming and control
Type
ArticleAuthors
Pistikopoulos, Efstratios N.Dominguez, Luis
Panos, Christos
Kouramas, Konstantinos
Chinchuluun, Altannar
Date
2012-04-21Online Publication Date
2012-04-21Print Publication Date
2012-05Permanent link to this record
http://hdl.handle.net/10754/599980
Metadata
Show full item recordAbstract
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.Citation
Pistikopoulos EN, Dominguez L, Panos C, Kouramas K, Chinchuluun A (2012) Theoretical and algorithmic advances in multi-parametric programming and control. Comput Manag Sci 9: 183–203. Available: http://dx.doi.org/10.1007/s10287-012-0144-4.Sponsors
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.Publisher
Springer NatureJournal
Computational Management Scienceae974a485f413a2113503eed53cd6c53
10.1007/s10287-012-0144-4