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.
|Original language||English (US)|
|Number of pages||21|
|Journal||Computational Management Science|
|State||Published - Apr 21 2012|
Bibliographical noteKAUST 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.